Temperature is one of the main factors affecting the accuracy and stability of quartz vibrating beam accelerometer, and the change of working environment temperature will cause the accuracy and stability of the accelerometer to decrease. In order to improve the accuracy of the accelerometer in a variable temperature environment, temperature-compensated technology can be used to reduce temperature-induced accelerometer drift. In order to realize the real-time accuracy compensation of MEMS quartz vibrating beam accelerometer, the frequency and temperature data of the accelerometer need to be collected simultaneously. In this paper, based on the advantages of FPGA parallel timing processing and the powerful computing and data processing capabilities of the embedded SOPC system, a frequency and temperature measurement IP core is developed to realize the acquisition and temperature compensation of accelerometer frequency data based on the data acquisition and accuracy compensation system requirements of MEMS quartz vibrating beam accelerometer. Through the temperature compensation algorithm model embedded in the system, the real-time online temperature compensation of the accelerometer is completed. The results show that the data acquisition and accuracy compensation system developed in this paper can realize the acquisition of frequency and temperature data, and the frequency measurement accuracy is better than 10^-6, and the temperature compensation algorithm model embedded in the system can realize the real-time online compensation of accelerometer accuracy.

The performance of quartz vibrating beam accelerometers is directly related to the performance of the driving circuit, so it is necessary to study how to improve the performance of the driving circuit. In this paper, the electrical characteristics of quartz vibrating beams is analyzed through theoretical, simulation, and experimental measurements. Based on this, a low-noise driving circuit for a quartz vibrating beam accelerometer with high-quality sine wave output is designed. This circuit uses a charge amplifier circuit to achieve low noise detection of quartz beam current, and introduces a static capacitance compensation circuit to improve circuit performance. The experimental results show that this driving circuit can drive the quartz vibrating beam normally, and the output is a standard sine wave without significant distortion. The spectral density of white noise is approximately 140 μHz/Hz^1/2, based on the scaling factor of the matching accelerometer 80 Hz/g, the equivalent acceleration resolution is 1.75 μg/Hz^1/2, which proves the rationality of theoretical analysis and circuit design.

Quartz vibrating beam accelerometer is the future development direction of high-precision strategic inertial navigation class accelerometer. Inertial navigation accelerometers have high requirements for the environmental adaptability of a single meter. The impact response of missiles and rockets generated at the launch moment and the huge overload impact put forward higher requirements for the mechanical reliability of accelerometers. The adaptability in complex environments of strategic model have a gap. strategic models are not used at present. In view of the large overload and large impact conditions during the use of the model, mass block design idea based on quartz flexible accelerometer with high technical maturity, a new vibrating beam accelerometer structure with double beam swinging tongue and four paws fixed is proposed. The high precision assembly scheme design of the structure is completed. Based on specific impact test spectrum,the design structure is simulation,the maximum displacement and stress of the mass block under the impact condition are obtained. The simulation results show that the accelerometer has the capability of resisting high overload and large impact spectrum of input 4500 g, based on the force hammer impact test, the designed accelerometer can withstand 600 g impact under damping conditions,enhance withstand 400 g of mechanical impact in related report,to solve the problem of poor resisance of quartz vibration beam accelerometer in application.

With the development of high-precision long endurance inertial navigation systems, vertical deviation gradually replaces inertial component error as the main source of error. The existing methods for obtaining vertical deviation mainly include measurement and indirect estimation, both of which highly rely on high-precision equipment or a large amount of high-precision real measurement data. This study is using exponential anomaly, second-order Markov anomaly, second-order Markov undulation, and third-order Markov undulation models to model vertical deviation, establish the relationship between terrain and statistical model characteristic parameters: root mean square of vertical deviation, and inverse correlation time. Based on the vertical deviation statistical model, further research is conducted on the error propagation characteristics of inertial navigation systems, exploring the quantitative relationship between velocity error, position error, and statistical model characteristic parameters. This research is enriching the interpretability of vertical deviation data and is providing a reference for simulation research of navigation systems.

The construction methods based on VCR model and BP neural network model are compared and analyzed to address the problem of temperature drift caused by temperature changes in the working environment of quartz vibrating beam accelerometer. The feasibility of the two compensation algorithms is verified through data samples. And an accelerometer performance testing system is built to verify the compensation effects of the two compensation methods. The experimental results show that the two compensation models can significantly improve the temperature stability of the accelerometer, with a decrease of nearly two orders of magnitude in the zero bias temperature coefficient and a decrease of one order of magnitude in the scale factor temperature coefficient. After temperature compensation in the VCR model, the zero bias temperature coefficient is 14.285 μg/℃, with a scaling factor temperature coefficient of -4.2×10^-6/℃. After temperature compensation in the BP model, the temperature deviation coefficient is 13.326 μg/℃, with a scale factor temperature coefficient of -8.808×10^-6/℃, the VCR model has shown certain advantages in scale factor compensation of quartz vibrating beam accelerometer.

Wireless charging technology is a kind of technology that realizes energy transmission through non-contact method, with the advantages of high safety and strong environmental adaptability, which is one of the key technologies to enhance the unattended capability of underwater autonomous vehicles(AUV). To meet the special requirements of anti-misalignment and miniaturization design of receiving device in wireless charging system, an AUV wireless charging system based on dynamic traveling wave magnetic field is proposed in this paper. Firstly, a new magnetic coupling device consisting of orthogonal transmitting and dipole receiving overlapping is designed. The two layers of transmitting windings are decoupled from each other to form a constant amplitude traveling wave under the space-time coordination mechanism to suppress output fluctuation. Then, a wireless charging system circuit based on current doubler is proposed and analyzed. Finally, an experimental platform is built to verify the feasibility of the proposed system. The results show that the system can deliver 1.2 kW to the load with a system efficiency of 87.04%, and especially the proposal achieves stable output in the range of rotational misalignment of [-30°, 30°] and axial misalignment of [-30 mm, 30 mm].

It is difficult to experience the complexity and variability of the modern battlefield in the set scenario of the simulation test, and it is difficult for a single unmanned system to adapt to the changing battlefield environment, so the unmanned cluster system has gradually become an important force in deciding the victory or defeat. Unmanned cluster cooperative navigation technology is one of the key technologies for unmanned system cluster energy efficiency. In view of the extensive involvement of unmanned cluster cooperative navigation technology in many application fields, this paper takes cluster UAVs as a typical example, analyzes in-depth the organizational configuration, navigation information resources, cooperative algorithms and optimization of unmanned cluster cooperative navigation technology, and discusses and looks forward to the future development trend of cooperative navigation in the light of the key problems it faces.

With the continuous development of underwater environment perception technologies, acoustic-based sensing methods have gradually become mainstream, benefiting from the long propagation distance and wide coverage of sound waves in water. Among various acoustic sensing technologies, forward-looking sonar, with its ability to detect objects in the field of view in real-time, plays a crucial role in underwater environment perception and has been widely applied in fields such as fisheries, maritime safety, and military operations. However, the performance of forward-looking sonar is limited by the acoustic propagation characteristics and interference from the complex underwater environment. Its high noise and low signal-to-noise ratio data present significant challenges for sonar imaging and target detection. While traditional sonar image denoising methods have been extensively validated and applied in practical scenarios, deep learning-based sonar image denoising technologies have shown more prominent advantages in dealing with the complex noise found in forward-looking sonar data. The field of forward-looking sonar target detection has undergone a revolutionary shift from traditional algorithms to deep learning methods, significantly improving detection accuracy and generalization capabilities. This paper reviews the development of sonar image denoising and target detection in both traditional and deep learning methods, systematically summarizes current research progress and methodologies, and highlights emerging innovations based on deep learning. It also analyzes the prospects for application in complex underwater environments and discusses potential future research directions, including data fusion, algorithm optimization, and challenges in real-world applications.

The localization and navigation performance is the core capability of mobile robots, and its evaluation standards are of great significance for the development of mobile robot technology and industry. This article investigates the current status of performance evaluation standards for mobile robot localization and navigation at home and abroad. Nine domestic and international standards are compared from the aspects of mobile robot localization performance, navigation performance, obstacle avoidance ability, etc. The comprehensiveness of testing performance, universality of testing conditions, and feasibility of testing methods in each performance evaluation standard are analyzed, providing useful references for mobile robot performance evaluation and engineering application standardization.

In this paper, according to the high-precision and low-stress assembly requirements of quartz vibration beams and quartz pendulums, a micro-assembly system for MEMS resonant accelerometers including dual microscopic vision, assembly motion control module, micro-absorption device, and rough positioning work platform is designed. The micro-vision positioning algorithm and precision motion control method are thoroughly studied, and a new method of micro-assembly of MEMS resonant accelerometers combined with low-temperature activation bonding process is proposed. MEMS resonant accelerometer micro-assembly experiments are carried out. The experimental results show that the micro-assembly precision of the sensor is less than 10 μm, which meets the demand of sensor assembly precision and effectively solves the problems of poor manual assembly precision of the sensor.

The number of seafloor acoustic navigation beacons determines the solvability of acoustic navigation. For example, when using a single seafloor acoustic beacon for navigation, it is necessary to integrate information such as the vehicle’s heading or attitude. The precision level of active sonar navigation system under varying numbers of seafloor acoustic navigation beacons is explored using vehicle state estimation model within a sliding window. Designing a simulation experiment to analyze the navigation accuracy of an active-sonar navigation model as the number of seafloor acoustic navigation beacons increased from one to four. The results obtained from the simulation experiment are further validated using actual measured data which show that: the accuracy of the active sonar navigation is directly proportional to the number of observable seafloor acoustic navigation beacons. When there are four beacons, the decrease in accuracy caused by reducing the number of beacons is within 1 m. However, the accuracy significantly decreases when there is only a single beacon, but the navigation accuracy can still be maintained within 10 m.

The primary challenge faced by the INS/GNSS is to achieve reliable and cost-effective positioning during GNSS outages. Under certain conditions, such as tunnels, tall buildings in urban areas, and adverse weather conditions, prolonged GNSS signal loss may occur, rendering the INS/GNSS fusion navigation system to degrade to a standalone inertial navigation system. To address this issue, a novel INS/GNSS fusion navigation algorithm based on GRU neural networks in the presence of GNSS denial is proposed. This algorithm operates by utilizing the inertial navigation parameters as inputs to the GRU neural network when GNSS signals are available, while simultaneously utilizing the three-dimensional position information provided by GNSS as the output of the GRU neural network and training it. Subsequently, when GNSS signals disappear, the inertial navigation parameters are used as inputs to the trained GRU model to obtain the three-dimensional position information of GNSS, enabling INS/GNSS fusion navigation even in the presence of GNSS signal denial. The simulation results, with a maximum positioning error of 5.646 m, demonstrate that this algorithm effectively ensures the accuracy and robustness of INS/GNSS fusion navigation under GNSS signal denial.

The whole angle mode hemispherical resonant gyroscope has the characteristics of wide measurement range, small size, high reliability and low cost, and has a wide range of application prospects in land, sea, air, space and other fields. Due to the unavoidable geometric errors and damage of the gyrometer head, it leads to large losses and uneven distribution of the circumferential damping of the meter head, which will lead to the locking area of the gyroscope and affect the application of the gyroscope. On the basis of analyzing the influence of damping inhomogeneity on gyro-locking area, the suppression effect of different rotational modulation schemes such as unidirectional rotation, square wave, triangular wave and sine wave on gyro-locking area is studied. A dual-axis rotation test platform is built, and tests such as the detection of the Earth's rotation angle rate, the nonlinearity of the scale factor and the detection of the lock area are carried out for the gyroscope prototype of the 0.1 mHz damping inhomogeneity. The experimental results show that the new swing rotation modulation lock area suppression method reduces the gyro lock area from 38 (°)/h to below 0.048 (°)/h, which lays a foundation for the engineering application of hemispherical resonant gyroscope in whole angle mode.

In order to solve the problem of selecting high-precision observation stars from multiple stars as navigation star points in the astronomical positioning of inertial navigation-aided star sensors, a stargazing accuracy evaluation method based on object image conjugation based on point light source was proposed. In this method, the star vector successfully recognized by the star sensor is converted into a horizon coordinate system parallel to each axis of the star sensor, and the stargazing accuracy is evaluated by calculating the values of the acute angles between the object vector and the image vector of the star recognition. After the accuracy evaluation, the observation star with high accuracy is used as the navigation star and applied to the astronomical positioning of the inertial-assisted star sensor. The results of field data processing show that the proposed method can effectively select navigation stars with high accuracy, and the positioning results of the selected navigation stars are higher than those obtained by astronomical positioning before selection, and the data variance and standard deviation are 1 to 3 orders of magnitude lower.

In order to achieve autonomous fault-tolerant navigation for vehicles in satellite signal rejection environment, an integrated navigation method using a strapdown inertial navigation system and distance sensor is proposed. For the velocity sensor, a vehicle Doppler velocity radar is selected, and for the distance sensor, an odometer is selected. The error analysis and modeling of strapdown inertial navigation system, Doppler velocity radar and odometer are carried out respectively, and the state equation of the integrated navigation is established by taking the errors of the strapdown inertial navigation system and others as states. The measurements of inertial/Doppler radar and inertial/odometer integrated navigation are respectively constructed by using the velocity and attitude output of strapdown inertial navigation system, the velocity output of Doppler velocity radar and the distance output of odometer, and the corresponding measurement equations are established. The federated filtering fault-tolerant structure is adopted to fuse the results of local filtering inertial/Doppler radar and inertial/odometer integrated navigation globally. The simulation results show that this method can not only achieve autonomous fault-tolerant navigation for vehicles, but also has high navigation accuracy. The positioning accuracy is better than 27.1 m without sensor failure, the heading accuracy is better than 5.6′, and the horizontal attitude accuracy is better than 0.2′, while the positioning accuracy is better than 49.6 m, the heading accuracy is better than 8.5′, and the horizontal attitude accuracy is better than 0.3′ in the event of a sensor failure.

Krylov angle method is a kind of method for strap-down inertial navigation attitude solution. In view of the existence of singular points in its differential equation, it is considered not suitable for the full attitude solution in the past. The analysis and verification show that the Krylov angle will stabilize in a new state after the mutation caused by singular points. At the same time, the coordinate transformation matrix remains unchanged, proving that the Krylov angle method can be applied to the full-attitude navigation solution. Since the differential equation of the Krylov angle contains trigonometric functions, it is difficult to solve. In this paper, a method based on segmentation, interpolation and variable slope integration is proposed. Firstly, the exact calculation formula of implicit Euler integral is derived, and then the interval is divided into sub-intervals for calculation. Finally, the test data of large dynamic test equipment is used for simulation, and the position error of the solution result is reduced from the order of hundred to the order of ten meters, which proves that the method proposed in this paper can realize the full attitude and high precision solution.

PNT services based on satellite navigation have been fully integrated into socio-economic development and national defense construction. Spatio-temporal information security has become an important part of national security. Aiming at the security problems faced by satellite navigation PNT services in daily applications and navigation confrontations, the requirements and task connotations of PNT services security assurance are given, the overall architecture of the security assurance system based on satellite navigation PNT services is constructed, and the construction and operation mechanism of the system are designed to provide support for the realization of China’s independent and controllable satellite navigation PNT services security.

Polar regions occupy a significant position in strategic, economic, and scientific research fields. Due to the unique natural environment of the polar areas, underwater vehicles have become key to human exploration and development of the poles. Affected by factors such as large-scale ice coverage and satellite denial, there are numerous challenges in the operation of underwater vehicles beneath the ice, with the primary issue being the acquisition of precise positional information of the vehicles. Sound waves are the only effective information carriers in the polar under-ice environment, and acoustic positioning and navigation technology is the main means for high-precision positioning and navigation of underwater vehicles. In this paper, the difficulties existing in the navigation tasks of polar under-ice vehicles are firstly analyzed, including the impact of high latitude effects, sustained low-temperature seawater, and large-scale ice coverage on the navigation and positioning technology of underwater vehicles. Then, the navigation methods of polar under-ice vehicles are reviewed and the current status and limitations of these methods in polar under-ice environments are analyzed. The research status of polar under-ice acoustic positioning and navigation technology is subsequently discussed, including main application cases and achieved performance outcomes both domestically and internationally. Finally, the challenges faced by polar under-ice acoustic positioning and navigation technology and its future development trends are summarized.

Due to the specific task limitations of underwater vehicles and the need for long endurance and covert navigation positioning, there are no prerequisites for the carrier to achieve position correction within the matching area in certain specific scenarios. To achieve entire course navigation positioning, a gradient difference entire course matching method based on particle mass filter algorithm is proposed. Extract the gravity anomaly characteristic parameters and adopt the comprehensive feature entropy weight method to select the matching area, effectively providing prior navigation area support for the implementation of the entire course gravity matching algorithm. According to gravity measurement circle probability error constraint, gradient difference is applied to gravity anomaly values to determine the sampling frequency of matching method. Fully explore the gravity anomaly information in the large background field and achieve adaptive frequency filtering in areas where gravity anomaly changes are not significant. The fully affine transformation using least squares optimization parameters is used to smooth the matching trajectory, ensuring the accuracy and stability of matching localization. The simulation experiment results show that the proposed algorithm can effectively control the matching positioning accuracy within half a grid, which can meet the navigation and positioning requirements of entire course gravity matching for underwater vehicles.

The multi-source fusion navigation system is prone to faults in practical applications, which can degrade the systems positioning performance. To enhance the reliability of the multi-source fusion navigation system and prevent faults from compromising navigation performance, an autonomous integrity monitoring method for multi-source fusion navigation based on MHSS-PCA is proposed. Firstly, according to the subsystem composition in the multi-source fusion navigation system, a fault detection method based on MHSS-PCA is constructed using the KF-LS approach, which detects and isolates faulty navigation sources. Secondly, a parallel w-detection method is used to establish a recovery verification mechanism, ensuring that once faulty navigation sources are restored, they can be reintegrated into the fusion calculation. Finally, based on the effective navigation sources in the system, a dynamic allocation criterion for integrity risk is established to calculate the system protection level in real time, achieving integrity assessment and alarming. In the marine scenario, simulation tests are conducted using real-time trajectory data. The test results show that the fault detection method based on MHSS-PCA effectively detects faulty navigation sources, with bias fault detection within 1 s and gradual fault detection within 6.5 s. Through the recovery verification mechanism, once the navigation source is restored, it is reintegrated into the fusion calculation within 3 s, thereby improving the reliability of the multi-source fusion navigation system.

The marine gravimeter is currently an important instrument for obtaining high-precision and high-resolution ocean gravity field information. The main marine gravimeters still rely on imports. As a self-developed marine gravimeter, CHZ-II has undergone multiple shipborne tests on the sea surface and achieved good results. Firstly, the structural composition and technical characteristics of the CHZ-II marine gravimeter are introduced. Then, the test results carried by the Xuelong scientific research ship are introduced. The internal consistency accuracy of three grid intersection points for the voyage are calculated, the accuracy of grid 1 is 0.73 mGal, the accuracy of grid 2 is 1.63 mGal, and the accuracy of grid 3 is 0.54 mGal, which are consistent with the overall trend of gravity anomalies in the Sandwell V32 satellite altimetry model. The Antarctic test of the Xuelong shows that the instrument has reached the same level of accuracy and stability as similar instruments at home and abroad, and can replace the current imported ocean gravimeters.

The lock-in effect largely determines the performance of mechanically dithered ring laser gyroscope. In order to reduce the over-locking time and improve the accuracy of gyroscopes, a frequency-multiplication dithering method with odd harmonic superposition is proposed. Firstly, the design criteria for the odd frequency-multiplication dither signal are presented, and the over-lock-in region characteristics of single and combined odd frequency-multiplication signals are analyzed. Secondly, the effects of the dither mechanism on the amplitude and phase of odd frequency-multiplication signals of various orders are analyzed, and a laser vibrometer is used to test the dither amplitude of the cavity under different orders of odd frequency-multiplication dithering. The results show that the optimal order of the odd frequency-multiplication signal can be selected based on the measured response amplitude in practical engineering applications. Finally, M-sequence noise is used to increase the random characteristics of the dither signal and simulations are performed. The simulation results indicate that compared with the commonly used sinusoidal dither signal, the accuracy of gyroscopes can be effectively improved by employing the odd frequency-multiplication dither signal proposed.

In order to meet the R&D needs of low-cost integrated fiber gyroscope, a PZT fiber phase modulator with small nonlinearity coefficient and stable performance is developed. A new structural design scheme of PZT fiber phase modulator with support bracket is proposed, and the structural parameter design and frequency characteristics analysis of the modulator are completed, and the performance optimization of PZT fiber phase modulator is realized. At the same time, in order to solve the problem of large nonlinear error of PZT fiber phase modulator, a phase hysteresis nonlinear feedback compensation scheme based on double closed-loop system is proposed, and the design of SOPC-based demodulation scheme is completed to compensate for the inherent hysteresis nonlinearity error of piezoelectric materials, so as to reduce the bias of the gyroscope and improve the bias stability. An integrated fiber optic gyroscope system based on integrated photonic chips is built, and the experimental results show that the zero drift of the gyroscope is 0.69 (°)/h for 10 s, and the technology effectively compensates for the influence of hysteresis nonlinearity error on the accuracy of the gyroscope.

The micro hemispherical resonator gyroscope(μHRG) is an innovative micro-gyroscope that leverages the Coriolis effect, offering advantages such as a simple structure, compact size, low cost, high accuracy, excellent stability, and robust resistance to interference. Due to its significant potential, numerous researchers have been dedicated to advancing μHRG technology with a focus on enhancing precision and stability. Firstly, the working principle of the μHRG is summarized in this paper. Then, the manufacturing processes of the resonator are categorized into three main methods: micro glass expansion method, high-temperature blowtorch blowing method and thin-film deposition method. For each process scheme, the latest research progress of is domestic and international research institutions is discussed in detail, the advantages and disadvantages of each manufacturing process scheme are summarized. Finally, the research direction of micro hemispherical gyroscope resonator is prospected.

Gravity-matched navigation technology is of indispensable value for error correction of inertial navigation systems due to its passivity, high stealth and strong anti-jamming properties. However, the traditional one-dimensional gravity matching algorithm is often limited in practical applications due to the frequent occurrence of mis-matching and the under-utilisation of two-dimensional gravity base map information. To address these problems, a new concept of gravity lighthouse navigation system is proposed in this paper, which deeply exploits and utilises the information in two-dimensional gravity basemaps in a face-matching manner. Firstly, high-quality fitness zones are accurately screened based on multi-attribute decision criteria, which are figuratively called “gravity lighthouses”. Subsequently, accurate navigation based on these “gravity lighthouses” is achieved by a two-dimensional image matching algorithm. The simulation experiment results show that the distance error obtained by the gravity lighthouse matching method is reduced by 62.22% compared to the original inertial navigation error. Compared with traditional one-dimensional matching methods, the accuracy of gravity lighthouse matching has been improved by 18.58%. The significant effect of this algorithm in reducing inertial navigation errors and improving navigation accuracy provides a new and effective approach for error correction in inertial navigation systems.

In low signal-to-noise ratio(SNR) situations, magnetic anomaly generated by magnetic target is usually buried in the magnetic noise, leading to a decline in the detection performance of traditional magnetic anomaly methods. To improve the detection performance of weak magnetic anomaly under low SNR, a weak magnetic anomaly detection method using ResNet-GRU network is presented in this paper. In this method, the Conv1D modules based on ResNet and the GRU modules are employed to extract multidimensional features from magnetic anomaly signals, enabling the detection of such signals through the fusion of multiple features. To train the model, a real-world magnetic anomaly dataset is constructed, consisting of 8646 positive samples and 8431 negative samples. Experimental results demonstrate that proposed method using ResNet-GRU has an accuracy of 90.39%, a precision of 91.33%, and an F₁ score of 90.18% on the test set, outperforming the performance of fully connected neural network model and one-dimensional convolutional neural network model. The proposed method has good detection performance of weak magnetic anomaly under low SNR.

The operation of underwater vehicles necessitates the implementation of navigation systems, which are responsible for the provision of positional data and the delivery of navigational services. It is not possible to provide effective satellite navigation services in an underwater environment, as the signals in question are unable to enter the water. In response to the demand for underwater navigation applications for underwater vehicles, the underwater variation characteristics of Loran-C signals are analyzed and an underwater Loran-C signal reception method is proposed. Firstly, the land propagation capability of the Loran-C system is investigated. Secondly, the influence for the Loran-C signal in an underwater environment is explored. Finally, the influence of dispersion effects on signal strength and perimeter difference under different water depth conditions is analyzed in detail. The simulation results demonstrate that as depth increases, the third cycle identification point of the underwater Loran-C signal is shifted forward, and the perimeter difference increases. Furthermore, the perimeter difference of the Loran-C signal exceeds the usage limit after 3 m underwater, resulting in signal unavailability.

MEMS quartz resonant accelerometer microassembly equipment is an automatic microassembly system integrating multi-function modules and key technologies, which has the characteristics of high precision and high efficiency. In this paper, a microscopic visual localization method applied to the system is developed. Firstly, according to the analysis of microassembly process, the precision positioning structure with upper and lower binocular microscopic vision is designed. Secondly, based on the nine-point calibration principle, the world coordinate system is established on the self-designed high-precision checkerboard calibration board. The conversion of camera pixel coordinate system to world coordinate system is realized. Finally, through CIE chromaticity map gray reconstruction and Canny edge detection algorithm, a high-precision recognition method of accelerometer assembly features is proposed. The experimental results show that the system’s microscopic visual positioning accuracy is better than 5 μm, and the assembly feature recognition time is less than 5 s.

According to actual situation that the traditional observability analysis method in the design of maneuver path can only obtain the observability of estimated parameters, but not the accuracy of the parameter estimation, a theoretical method of variance prediction based on observability is proposed. Firstly, the observability analysis method based on the least squares estimation theory is illustrated. Secondly, the proposed variance prediction theoretical method is derived and proved, its physical meaning is elucidated, and the predictive error model is analyzed. Finally, the INS multi-position alignment is taken as an example to validate the application of the method, which is proved to be effective. The method can predict the real-time variance of state parameters before Kalman filtering, which provides an important basis for the design of the maneuver path and the prediction of estimation accuracy.

MEMS gyroscopes belong to Coriolis vibratory gyroscopes, featuring advantages of small size, low mass, and low power consumption. With the development of MEMS design technology and domestic manufacturing processes, the zero-bias noise level of MEMS gyroscopes continues to decrease, having the potential to achieve navigation-grade performance. The research progress in the field of high-precision MEMS gyroscopes by domestic and foreign research units in recent years is introduced in this paper. The technical characteristics and development status of Type II gyroscopes represented by ring gyroscopes, quadruple-mass gyroscopes, and double Foucault pendulum structures, as well as Type I gyroscopes represented by fork structures reported by Honeywell and Polytechnic University of Milan are summarized. The key technical advantages and challenges faced by Type I and Type II gyroscopes at the current stage are discussed, which providing references and insights for domestic and foreign peers to carry out scientific research on this type of gyroscope structure and improve the performance of MEMS Coriolis vibratory gyroscopes.

Navigation technology provides critical kinematic information and fundamental spatio-temporal references for human survival and development. In this paper, the evolution of classic navigation devices and physical principles is explored from three perspectives: application, scientific foundations, and functionality. By analyzing developmental patterns and structuring historical periods, the essential characteristics of navigation technology progression are outlined and its future progress trajectory is predicted. Furthermore, focusing on cutting-edge advancements in artificial intelligence, the emerging opportunities and challenges in construction of next-generation national comprehensive positioning, navigation, and timing(PNT) end-users are thoroughly studied. A transformative shift towards autonomy, multi-source and intelligent characteristics is highlighted, which provides strategic insights for innovation and development of future navigation systems.

Quartz vibrating beam accelerometer (QVBA) has become a research focus due to its high precision and stability. To address the challenges of difficulty in improving the scale factor of QVBA, a novel monolithic QVBA is proposed and developed. In this paper, the structure of the monolithic QVBA is introduced and the theoretical analyses is conducted, therefore the feasible approaches to improve the scale factor is pointed out. Finite element simulation analysis is performed to determine the specific structure of the accelerometer, and sensitive structures are fabricated using wet etching processes followed by vacuum packaging. Experimental results indicated that a scale factor up to 254.4 Hz/g, a scale factor stability of 2.8×10^-6 and a bias stability of 4.4 μg are achieved. The results demonstrate that the proposed monolithic quartz vibrating beam accelerometer features a large scale factor and high stability, making it suitable for high-precision inertial navigation systems.

Aiming at the existing miniaturised frequency measurement circuit applied to the back-end of the vibrating beam accelerometer with low accuracy, an analogue interpolation method using analogue devices piggybacking to achieve accurate frequency measurement is proposed, and this experiment adopts the FPGA and analogue devices to cooperate to complete the measurement of the signal to be measured and the data pipelined processing and arithmetic. The output of the standard signal source and the output of the vibrating beam accelerometer are measured using the isoperiodic method and the analogue interpolation method, respectively. The experimental results show that the analogue interpolation frequency measurement method is significantly better than the isoperiodic frequency measurement method: when using a standard signal source as the input, the average fluctuation amount compared to the isoperiodic method is reduced from 0.63 mHz to 0.012 mHz, and the stabilisation accuracy is improved by 52.5 times. When measuring the output of the vibrating beam accelerometer, the average fluctuation compared to the results of the equal period method is reduced from 2.5 mHz to 0.98 mHz, and the stability accuracy is improved by 2.6 times, the frequency of the system clock is increased from 22.1184 MHz to 150 MHz to continue the test, and the stability accuracy is further improved by 2.7 times, and the results are applied recursive average filtering process to achieve an average fluctuation of 0.11 mHz. The experimental results of the frequency measurement method of the vibrating beam accelerometer based on the simulated interpolation method show that the frequency measurement accuracy can be improved by using the hardware to control the counting time, which can be achieved by applying it to the device or the arrow, and there is a lot of room for optimisation in terms of accuracy.

In response to the issue of describing the physical characteristics of micro-electromechanical inertial measurement units, a mathematical model construction method of IMU is proposed. By establishing a finite element analysis model of the IMU and conducting multi-physics simulations, the response characteristics to acceleration and angular acceleration excitation are obtained, and the transfer function models are established. A temperature response model is established through temperature experiments, and a temperature-dependent model of inertial cross-sensitivity is obtained through thermo-solid coupling simulations. The static sensitivity and dynamic response models of inertial components are established through calibration experiments and linear vibration/angular vibration experiments. The constructed mathematical model is tested, and the results show that it can reflect the internal physical state of the IMU and the inertial measurement errors, and can be used for error analysis and system simulation.

The differential GPS measurement system firstly uses a differential GPS base station with known accurate three-dimensional coordinates to obtain the positioning correction value, and then sends this correction value to the GPS mobile station to correct the measurement data of the GPS mobile station to improve the accuracy of GPS positioning. In this paper, the principle of differential GPS positioning is introduced. Relying on the geological survey project, the differential GPS positioning system is applied to the navigation of the helicopter aviation gravity measurement system, and attempts to establish an aviation gravity measurement system with differential GPS positioning navigation based on the helicopter platform. The integration method of the differential positioning system in the helicopter aviation gravity measurement system is explained through the establishment of base stations and mobile stations, and the positioning accuracy of differential GPS navigation is analyzed by solving data. The results show that compared with single-point GPS measurement, the positioning accuracy of differential GPS measurement is changed from 10 m to 0.1 m, which meets the requirements of aviation gravity measurement system for GPS positioning accuracy.

The ocean absolute gravimeter is a metrological instrument for the on-site calibration of current marine gravimeters based on the principle of relative measurements. A software and hardware design scheme for a high-speed interference signal acquisition system based on field programmable gate array(FPGA) is proposed to address the measurement characteristics of high-precision and high-frequency ocean absolute gravimeters. The selection and design of hardware circuits such as high-precision analog-to-digital converter conditioning and operational amplifier circuits have been completed. The logic control of USB3.0 data high-speed transmission module is realized by Verilog hardware description language. Then, a host computer with perfect functions and high visualization degree is developed by C# language to realize the processing and solving of gravity data. Finally, the test platform of the measured signal system is built based on the ocean absolute gravimeter. The test results show that the standard deviation of gravity obtained from 200 times absolute gravity measurements is 0.6 mGal and the class A uncertainty is 42.4 μGal. The designed acquisition system can meet the requirements of high frequency and mGal measurement accuracy of marine absolute gravimeter, and the research results can provide guarantee for the effective measurement of marine absolute gravity.

Single-pixel imaging (SPI) has introduced new breakthroughs in optical imaging, especially in overcoming the limitations of traditional optical microscopy. This study addresses the challenges of obtaining high-quality images under low-light conditions in conventional microscopy by developing a microscope imaging system based on SPI. The system employs a modular optical design combined with six advanced algorithms, including Alternating Projection, Differential Ghost Imaging, and Gradient Descent, to evaluate its performance. Experimental results show that under extremely low-light conditions of 0.9M counts per second (CPS), the system achieves single-pixel imaging with a sampling rate of 25%, reaching a resolution of 39.37 μm. The field of view can be adjusted between 22.09 mm² and 231.04 mm². Unlike traditional approaches involving enhanced light sources or fluorescence labeling, our method leverages single-photon detection and compressed sensing image processing algorithms to achieve high-quality microscopy under low-light conditions without causing photobleaching or phototoxicity. This effectively avoids light-induced damage to the sample. The proposed SPI-based microscopy method provides an innovative and efficient solution for imaging in extremely low-light environments.

In the use of Beidou receivers, the high dynamic characteristics of the system cause Beidou satellite signals to rapidly changing Doppler translations and code phases, which increases the difficulty of signal acquisition. The currently used PMF-FFT acquisition method consumes a large amount of hardware resources and running time, and is difficult to meet the speed requirements of Beidou receivers. In order to achieve Beidou signal acquisition in high dynamic scenarios, an capture algorithm based on improved PMF-FFT is proposed. Based on a detailed analysis of the mathematical theory of PMF-FFT, the correlator usage and noise interference of the acquisition system are reduced by integrating the internal storage of a single symbol. At the same time, multiple sampling clocks are introduced to ensure the clock conditions for chip integration. Finally, under the Beidou high dynamic scene, simulation is used to test the performance of this algorithm and the traditional algorithm. The results show that compared with the traditional algorithm, the noise suppression ratio of this algorithm is improved by about 1.3 dB and the running time is shortened by 7%. Therefore, this algorithm can reduce the use of correlator resources and improve the signal-to-noise ratio, and is suitable for Beidou under high dynamic conditions.

In complex indoor environments where GNSS signals are rejected, ultra wideband(UWB) technology has attracted much attention for its advantages such as having high accuracy and high stability. Aiming at the problem of unmanned vehicle localization in indoor complex environments, a combined INS/UWB/altimeter/magnetic compass navigation algorithm based on adaptive federated Kalman filter algorithm for line-of-sight reconstruction(Re-Los-AFKF) is proposed based on inertial navigation system and UWB. The algorithm establishes the mathematical model of each sub-filter and uses a vector-based adaptive information allocation factor algorithm. The INS/UWB tight combination sub-filter is designed to predict the position parameters of the unmanned vehicle by using the characteristics of INS with high short-time accuracy to realize the non line-of-sight(NLOS) error detection in the UWB ranging information, use the data of adjacent moments to reconstruct the NLOS information for the line-of-sight(LOS) range, and carry out the over-compensation identification and the over-compensation correction for the reconstructed distance information. The experimental results show that the localization accuracy of the Re-Los-AFKF algorithm is comparable to that of high double sided two-way ranging(HDS-TWR) and movmean-federated Kalamn filter(MFKF) in LOS environment. In the complex NLOS environment, Re-Los-AFKF reduces the mean value of error in horizontal position by 46.24% and 29.35%, and reduces the RMS of error in horizontal position by 41.40% and 29.18% compared to HDS-TWR and MFKF, respectively. In summary, it is shown that the algorithm is not only capable of stable localization in LOS environment, but also has good localization performance in NLOS environment, which has certain adaptability, robustness and engineering applications.

The servo stability loop constitutes a pivotal component within the high-precision inertial navigation systems, where its performance significantly influences the navigation accuracy. The friction interference torque emerges as a primary external disturbance within the servo stability loop, exerting considerable impact on the error dynamics of the platform stabilization loop. Consequently, addressing the compensation of friction and mitigating its effects on the servo stability loop is identified as an urgent and critical issue. Given the challenges associated with modeling and compensating for friction interference at the shaft end, this study delves into the friction model parameter identification and friction compensation control methodologies. Through the establishment of the LuGre axial friction model, predicated on the outcomes of the identification process, this research utilizes the friction feedforward compensation approach based on the LuGre model to enhance the servo stability loop, which integrates a fiber-optic gyroscope. The efficacy and enhancement in reliability and accuracy of the inertial navigation system are substantiated through the Simulink simulation results. When the input step disturbance torque amplitude is 0.06 N·m, the angle position error decreases by 14.33" and 47% after adding friction feedforward compensation.