05 June 2026, Volume 25 Issue 3

    

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Special Issue: Autonomous Navigation Technology for Personnel in Sheltered Spaces
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  An Autonomous Localization Method for Sheltered Spaces Based on Artificial Geoelectric Field

  ZHAO Hui, BIAN Jiaxing, LING Zhongao, SU Zhong, LIU Ning, CHU Sirui

  Navigation and Control. 2026, 25(3): 1-12. https://doi.org/10.3969/j.issn.1674-5558.2026.03.001

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  Though satellite positioning, inertial positioning, wireless positioning and other technologies have been deeply penetrated into the fields of fire rescue, geological exploration, military equipment and so on, the problem of autonomous localization for personnel in underground and sheltered spaces has not yet been effectively solved. Inspired by the indoor localization of Wi-Fi, an autonomous localization method based on artificial geoelectric field for underground and sheltered space is proposed based on the fully explored geoelectric field distribution characteristics. This method does not require any auxiliary facilities to be set up in the underground and sheltered space, and constructs an artificial geoelectric field by injecting electric current into the earth, realizes the estimation of the distance from the detection point to the electric current injection point by detecting the electric field strength information of the geoelectric field. Then, this method realizes the accurate acquisition of personnel location information by fusing the distance information and coordinate information of multiple injection points based on the multilateral optimization positioning method. A geoelectric field positioning validation experiment with a range of 150 m×80 m is carried out in the field site, and the experimental results show that the localization method based on artificial geoelectric field can effectively obtain the personnel location information, with an average positioning error of 7.829 m and a single-point positioning accuracy of up to 1.352 m. The localization method based on artificial geoelectric field is expected to solve the problem of autonomous localization for personnel in underground and sheltered space environments, which has important theoretical research significance and engineering application value.
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  Pedestrian Dead Reckoning Based on Collaborative Smart Wearable Devices

  WANG Yifan, CHEN Shiyi, KUANG Jian, NIU Xiaoji

  Navigation and Control. 2026, 25(3): 13-22. https://doi.org/10.3969/j.issn.1674-5558.2026.03.002

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  The rapid expansion of smart wearable device market has intensified the demand for pedestrian positioning. In GNSS-denied environments, existing pedestrian dead reckoning(PDR) technologies are constrained by the strict requirement for rigid attachment between the device and the human body, leading to unstable heading estimation. Current alternative solutions also face limitations, struggling to satisfy consumer-grade requirements for convenience and positioning performance. To address these issues, a multi-device collaborative dead reckoning method is proposed in this paper. Based on the hypothesis of average heading consistency across gait cycles for different body parts during normal walking, the method fuses heading data from head-worn, handheld, and wrist-worn nodes. It dynamically detects changes in device mounting modes, performs mounting angle compensation and transfer, and suppresses heading divergence caused by mode transitions. Experimental results over a 400 m walk show that the collaborative positioning accuracy improved by 58.62%, 64.08%, and 42.80% compared to individual wrist-worn, handheld, and head-worn nodes, while heading estimation accuracy also improved by 65.13%, 60.63%, and 43.40%, respectively. This approach offers advantages in low cost and universality, providing a new perspective for indoor navigation on consumer-grade wearable devices.
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  Inertial Pedestrian Positioning Method Resistant to Carrier Motion in Elevator Scenarios

  ZHANG Wenchao, CAO Lei, WEI Dongyan, YUAN Hong

  Navigation and Control. 2026, 25(3): 23-32. https://doi.org/10.3969/j.issn.1674-5558.2026.03.003

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  In indoor or satellite environments-denied, the foot-mounted inertial pedestrian dead reckoning(PDR) based on zero-velocity update(ZUPT) is the mainstream technology for pedestrian autonomous positioning. However, when pedestrians move at a constant speed with a moving carrier (such as a box elevator), due to the lack of obvious inertial changes, the traditional ZUPT algorithm may misjudge that the pedestrian is in a zero-velocity state(“pseudo-stationary”), leading to significant positioning drift. To address this key issue, an inertial PDR positioning method resistant to carrier motion is proposed in this paper. Taking the typical indoor carrier, the box elevator, as an example, a detection algorithm for the carrier’s motion states (acceleration, uniform speed, and deceleration) based on the “trapezoidal” fluctuation characteristics of the vertical specific force in the navigation frame (n-frame) is innovatively proposed. Furthermore, motion constraint models based on the rated speed in the elevator industry specifications and the inertial integral speed are respectively constructed and effectively into the extended Kalman filtering framework to accurately constrain the divergence of the positioning error for pedestrians during the carrier’s uniform motion. In the tests in an actual office with building elevator scenarios, the proposed method significantly outperforms the traditional ZUPT and barometric fusion methods. In the elevator-riding test on an eight-story building(with a vertical height difference of 29.12 m), the height estimation error is effectively controlled at around 1 m, which verifies the effectiveness of the method.
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  Research on Optimization Algorithm for Collaborative Positioning of Rescue Personnel in Semi-obstructed
  Environments

  DU Shaoyang, ZHAO Yiyang, CHE Yiting, JI Miaoxin, LI Qianlei, LU Mingkun

  Navigation and Control. 2026, 25(3): 33-41. https://doi.org/10.3969/j.issn.1674-5558.2026.03.004

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  In complex emergency rescue scenarios such as semi-obstructed industrial sites, personnel positioning is easily affected by obstructions and signal attenuation, which makes traditional positioning solutions relying on fixed base stations difficult to be rapidly adapted to sudden rescue needs. While inertial navigation systems(INS) can provide autonomous positioning, they are afflicted with shortcomings such as cumulative errors over time and insufficient three-dimensional positioning accuracy. To address the issues of insufficient collaborative positioning accuracy and reliance on pre-existing infrastructure in emergency rescue operations within semi-obstructed industrial sites, a multi-person collaborative positioning technology combined with “ZigBee+INS” is focused on this study. The aim is to overcome the limitations of traditional positioning methods, as rapid deployment and high-precision positioning are enabled without the need for pre-established base stations, thereby rescue efficiency is improved and personnel safety is enhanced. Firstly, ZigBee anchors are deployed on the rescue personnel’s end, and the cross-power spectrum phase method is used to estimate the time delay of the time difference of arrival(TDOA). Secondly, by combining the location information of the rescue personnel and the commander, an improved TDOA algorithm is employed to suppress positioning errors. Thirdly, based on the results of the improved TDOA, the Taylor algorithm is used to determine the initial positions of the rescue personnel. Finally, position and heading constraints are established using ZigBee, barometers, and magnetometers, and multi-source information fusion and real-time position updates are achieved through an extended Kalman filter(EKF). Experimental results show that, compared with inertial navigation and classical collaborative positioning algorithms, the root mean square error and the absolute mean positioning error of the proposed algorithm are reduced by 55.42% and 62.36%, respectively. This algorithm achieves anchor-free and rapidly deployable multi-person collaborative positioning in semi-obstructed environments, and technical support is provided for precise command and control in emergency rescue operations.
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  Pedestrian Dead Reckoning Method Integrating Gait Features and Visual Information

  TIAN Tianqi, HU Yanzhu, MO Zhaofeng, XIAO Lishu

  Navigation and Control. 2026, 25(3): 42-50. https://doi.org/10.3969/j.issn.1674-5558.2026.03.005

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  After underground spaces suffer disasters, infrastructure outages and spatial structure collapses are prone to occur, rendering existing infrastructure-dependent personnel positioning methods inoperable. To address the demand for rescuers’ positioning in post-disaster underground spaces, a pedestrian dead reckoning(PDR) method integrating gait features and visual information is proposed in this paper. Based on multi-source autonomous signals from accelerometers, gyroscopes, cameras, and other sensors, the method introduces an adaptive step interval segmentation strategy into traditional PDR and adds a step length constraint mechanism to traditional visual positioning. It adopts cubature Kalman filter to realize data fusion of the two algorithms, thereby estimating the position information of personnel in underground spaces. The fusion algorithm is integrated into an intelligent vest and verified through experiments. Results show that the proposed method achieves a lower average positioning error than traditional PDR method and visual positioning method, with reductions of 77.27% and 46.18% respectively. The positioning accuracy is significantly improved, and the method is independent of external infrastructure, enabling accurate position information provision for personnel in underground spaces.
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  Application of Multi-strategy Secretary Bird Algorithm in Obscured-space Path Planning

  HU Lin, XIONG Ming, WANG Lijie, NIE Shiji, LYU Kelin

  Navigation and Control. 2026, 25(3): 51-63. https://doi.org/10.3969/j.issn.1674-5558.2026.03.006

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  Obscured-spaces generally denote complex environments—such as indoor areas, underground facilities, canyons, or dense forests—where global navigation satellite systems(GNSS) provide weak or unavailable positioning signals. In such settings, personnel autonomous navigation often suffers from irregular paths, unstable obstacle avoidance, and slow convergence due to the lack of GNSS, cluttered obstacles, and complex layouts. To tackle these issues, a multi-strategy adaptive secretary bird optimization algorithm (MSA-SBOA) is proposed in this paper. The approach begins with a dual-modal hybrid initialization strategy to increase population diversity. It then establishes a parameter memory pool to dynamically adjust key parameters and enhance iterative efficiency. Additionally, a differential crossover mechanism derived from evolutionary algorithms is integrated to further improve search capability and solution quality. Evaluation on the CEC benchmark suite confirms that MSA-SBOA achieves superior convergence speed and precision compared to the original secretary bird optimization algorithm. In obscured-space simulation, the proposed method generates shorter and smoother paths with higher obstacle avoidance rates. Owing to the potential risks and unpredictability of conducting human trials under such conditions, a bipedal robot—which mimics human movement speed and perceptual constraints—is deployed for physical validation. Experimental results demonstrate the feasibility and effectiveness of MSA-SBOA in real-world obscured-space path planning, offering robust algorithmic support for personnel autonomous navigation.
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  Collaborative Vision-based Localization in Vehicular Networks: A Stochastic Geometry Approach

  GUO Jingyi, SONG Xiaoshi, HUANG Xulun, ZHOU Ke

  Navigation and Control. 2026, 25(3): 64-70. https://doi.org/10.3969/j.issn.1674-5558.2026.03.007

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  In autonomous driving and intelligent transportation systems, visual localization estimates vehicle pose by recognizing environmental landmarks using onboard vision sensors, while cooperative localization enhances positioning continuity and reliability in landmark-sparse scenarios through inter-vehicle information sharing. To address the challenge of global navigation satellite system(GNSS) denials, a cooperative vision-based localization analysis framework tailored for vehicular networks is proposed in this paper, and a unified stochastic geometry-based modeling and performance evaluation system is established. The spatial distribution of environmental landmarks is modeled via a homogeneous Poisson point process(HPPP), and vehicle locations are characterized by a Poisson line Cox process(PLCP). On this basis, the single-vehicle visual localization probability is derived, and a V2V-based cooperative localization mechanism is introduced when visual perception fails, incorporating Nakagami-m fading channels to obtain a closed-form expression for the cooperative localization probability. Simulation results demonstrate that the theoretical analyses match the Monte Carlo simulations with a mean square error below 1%, validating the accuracy of the proposed model. The framework reveals the coupled effects of landmark distribution, channel fading, and vehicle layout, thereby providing theoretical guidance for performance evaluation and parameter optimization of cooperative vision-based localization.
Others
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  Magnetometry Based on Solid-state Spin System

  JING Ke, RONG Xing

  Navigation and Control. 2026, 25(3): 71-85. https://doi.org/10.3969/j.issn.1674-5558.2026.03.008

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  Magnetism is one of the fundamental properties of nature. Magnetometry holds significant value in both fundamental scientific research and technological applications. From geomagnetic detection and magnetic navigation to microscopic analysis of magnetic materials, pursuing characteristics such as high sensitivity and high spatial resolution is a key development direction for current magnetic field measurement technology. With the emergence of quantum sensing, magnetometry based on solid-state spins has garnered widespread attention and undergone rapid development due to its high sub-picotesla sensitivity, atomic-scale spatial resolution and the capability for in-situ operation under extreme environments. Focusing on solid-state spin systems, the advancements of magnetometry based on solid-state spins are summarized, beginning with an overview of their optical and spin properties.
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  Maritime Target Recognition Algorithm Based on Hybrid Preprocessing System

  HE Sihua, ZHANG Yu, CONG Bin

  Navigation and Control. 2026, 25(3): 86-93. https://doi.org/10.3969/j.issn.1674-5558.2026.03.009

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  With increasing demands for higher accuracy in maritime target recognition and the emergence of challenges such as difficulty in recognition when there is relative motion between the imaging system and the target, improving the formation accuracy of maritime vessels and system response capabilities has become an urgent technical challenge that needs to be addressed. To improve the accuracy and real-time target recognition capabilities of vessel formations, enhance precise maneuvering capabilities, and increase navigation safety, a maritime target recognition algorithm based on a hybrid preprocessing system is proposed to address the challenges of difficult target detection and low recognition accuracy faced by ship-mounted image sensors in rough sea conditions. The algorithm employs image sharpening, contrast enhancement, principal component analysis, and texture feature extraction for preprocessing, and improves the YOLOv3 algorithm to enhance maritime target recognition capabilities. Experimental results demonstrate that the algorithm achieves a target detection rate of over 90% with correct recognition results and can meet the requirements for autonomous navigation.
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  High-precision North-finding Technology Based on Micro-hemispherical Resonant Gyroscopes

  ZHANG Yongmeng, XUE Chi, WANG Qinghua, YU Sheng, SUN Jiangkun,
  WU Xuezhong, XIAO Dingbang

  Navigation and Control. 2026, 25(3): 94-100. https://doi.org/10.3969/j.issn.1674-5558.2026.03.010

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  With the growing demand for high-precision north-finding capability of weapon systems in modern warfare, the requirement for high-performance, integrated gyroscopic north finders has become increasingly urgent. The micro-hemispherical resonant gyroscope (μHRG),with its advantages of compact size, low cost, and excellent structural symmetry, has emerged as an ideal choice for developing compact, miniaturized north-finding systems. Nevertheless, its bias error severely restricts the overall accuracy of north-finding systems. To mitigate the impact of bias error, the influence mechanism of μHRG bias error on north-finding system is firstly investigated, and a north-finding accuracy model is established. Subsequently, a multi-position harmonic error compensation method is proposed according to the bias error characteristics of μHRG. Finally, the proposed method is experimentally validated. North-finding experiment results demonstrate thatthe μHRG-based north-finding system achieves an accuracy of 0.168° within 5 min using the multi-position harmonic error compensationmethod, which validates the effectiveness of the proposed method and provides strong technical support for overcoming performance limitations in μHRG-based north-finding.
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  Thrust Vector Tracking Control Method with Accelerometer Output Error Suppression

  XIONG Sicheng, GU Yapei, YAN Guangya, PENG Zhaoqin, ZHANG Jinyun

  Navigation and Control. 2026, 25(3): 101-110. https://doi.org/10.3969/j.issn.1674-5558.2026.03.011

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  When the existing inertial measurement unit works in the space-stabilized or strapdown working mode, the sensitive axis of quartz accelerometers cannot be aligned with the thrust vector direction. This not only degrades the output accuracy of quartz accelerometers affected by the cross-coupling quadratic term error, but also prevents gyro accelerometers to take advantage of its high overload accuracy under low axial overload conditions, meanwhile affects the navigation solution accuracy. Aiming at the above problems, a thrust vector tracking mode is proposed in this paper. The classical lead-lag control method is adopted to control the radial quartz accelerometers to the zero-overload direction, ensuring that the axial accelerometer tracks the thrust vector direction. This can eliminate the quadratic term measurement error of the quartz accelerometer. Experimental verification shows that the axial accelerometer can consistently track the overload direction, and the overload sensed by the radial accelerometer can be maintained at zero under the vector tracking mode. In addition, the high-precision inertial measurement unit is equipped with a gyro accelerometer. Considering the additional output error of the gyro accelerometer introduced by the base angular motion during the thrust vector tracking control process, an output error model is established, and the gain-scheduled linear quadratic regulator (GS-LQR) is adoped to optimize the control design of the thrust vector tracking process and suppress the output error caused by the base angular motion. Simulation results show that, compared with the implemented classical lead-lag vector tracking control method, the proposed method can effectively suppress the output error of the gyro accelerometer while maintaining an equivalent tracking speed.
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  Adaptive Compensation for Gain Variation in Digital Servo Loop of Three-axis Inertial Navigation System

  GAO Rongrong, WEI Zongkang, WANG Erwei, PENG Di, YAN Guangya

  Navigation and Control. 2026, 25(3): 111-119. https://doi.org/10.3969/j.issn.1674-5558.2026.03.012

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  The traditional three-axis inertial navigation system generally limits the rotational range of the inner frame axis and lacks consideration of the stability for the servo loop caused by the cross-coupling of the frame moment of inertia. Aiming at the cross-coupling problem of the frame moment of inertia caused by structural changes during the frame rotation process of three-axis inertial navigation system, a frame moment of inertia decoupling and compensation method based on frequency-domain series compensator is proposed. Firstly, the decoupling position of the frame moment of inertia is determined through the three-axis inertial navigation motion relationship model. Secondly, the decoupling matrix of the frame moment of inertia based on the mechanical model is obtained by using the series compensator decoupling method. Furthermore, in order to avoid the problem of inaccurate moment of inertia testing, the gain variation is numerically calibrated through test to obtain a fitting function with the inner frame axis angle as the independent variable and the gain variation value as the dependent variable, which adaptively compensates for the gain variation of the servo loop. Finally, the adaptive compensation method is verified through simulation and test. The test results show that after compensating for the frame moment of inertia, the amplitude margin at 70° of the inner frame axis angle increases from 4.2 dB to 7.7 dB, meeting the basic performance requirement of an amplitude margin of 6 dB. It realizes the compensation for the gain value variation of the multi-input multi-output servo loop and the compensation for the cross-coupling torque between each frame axis.