Local Navigation Research Articles

Partial Solar Eclipse Affects <i>Apis Mellifera</i> L Forging Activity

Bees use sun’s position for navigation and thus a solar eclipse may affect this capability. Present study was conducted during partial solar eclipse on June 21, 2020 at Ludhiana, Punjab. Apis mellifera L foragers’ activity at the hive entrance was recorded through a digital bee counter. Bees’ activity increased normally, i.e. 771 and 823 bees/ 15 mins coming in and going out of the hive, respectively before the start of eclipsephase. At peak obscuration it decreased slightly but non-significantly. Changes in hive temperature andhumidity might have limited the recruitment of foragers. Hence, no peak activity was recorded duringpeak obscuration, which otherwise was recorded on ordinary days at 1345 hr.

Commutative encryption and watermarking algorithm based on compound chaotic systems and zero-watermarking for vector map

Commutative encryption and watermarking (CEW) is an efficient and safe protection technology combining cryptography and digital watermarking. It features the dual functions of secure transmission and copyright safeguarding. In traditional CEW algorithms for vector map, the watermark is embedded by modifying the host data, which cannot meet the needs of high precision vector map, especially for vector maps applied in military and navigation positioning fields. To fill this gap, a CEW algorithm for vector map based on zero-watermarking and permutation encryption is proposed. Firstly, compound chaotic systems are applied to permutation encryption to encrypt the storage order and position of the vertex coordinates respectively. The key is generated by the SHA-256 hash method, which has higher security. Secondly, the number of vertex features is regarded as the feature invariants to establish the watermark information and watermark index. After that, the zero-watermarking image is constructed through the XOR operation of the feature matrix and the copyright information matrix. Experiments show that the combination of permutation encryption and zero watermark can better meet the needs of secure transmission and copyright protection of high-precision vector graphics. The security, robustness and watermark capacity of the algorithm have been improved, making it more practical.

Distributed satellite system autonomous orbital control with recursive filtering

In this article, we propose a recursive orbital elements filter for autonomous control of Distributed Satellite Systems (DSS) that significantly reduces the variance of relative orbital elements between the observed and the desired satellite orbits. Leveraging satellite kinematics and control inputs data, combined with a model of relative dynamics, the filter provides smooth and continuous orbital control, while minimizing propellant consumption. In conjunction with Precise Point Positioning (PPP) navigation, the proposed filter enables onboard continuous low-thrust control compatible with high-performance electric propulsion. We also propose a restricted transverse/normal control law that simplifies the thruster's configurations and/or attitude manoeuvres required for propulsion pointing. The applicability and validity of our proposed techniques are verified by numerical simulations with two case studies: a constellation for Differential Interferometric Synthetic Aperture Radar (DInSAR) for global infrastructure monitoring; and a maritime domain awareness mission based on along-track interferometric synthetic aperture radar which requires single-pass interferometry for responsive ship traffic surveillance, and the coverage of a very large maritime zone with high revisit rates.

Application of automatic driving task serialisation monitoring for operating robots

Abstract With the increasing application of industrial robots, more and more simple and repetitive operations in industrial automated production lines are replaced by industrial robots. In this study, a path planning algorithm is proposed for the autopilot task of an operating robot to find the optimal path from the start point to the goal point under the constraints of safe obstacle avoidance, shortest distance, and fastest time. Forward kinematics is used to detect whether it will collide with environmental obstacles until the first feasible result is detected as the end position for navigation. Serialized monitoring is used to obtain the activity information of each computational node, the hardware state information of the system, and the state of the autopilot task processing. Finally, obstacle avoidance navigation experiments on a mobile operating robot are conducted to verify the effectiveness and feasibility of the obstacle avoidance navigation algorithm. The results show that the maximum error of the autopilot task of the operating robot is 2.91cm, and the average error is 0.13 2cm, which is in line with the trajectory tracking error requirements of the operating machine control method and verifies the validity and practicability of this study.

Agricultural Vehicle Automatic Navigation Positioning and Obstacle Avoidance Technology Based on ICP

Agricultural Vehicle Automatic Navigation Positioning and Obstacle Avoidance Technology Based on ICP

The co-development of a mobile navigation app in an integrated care network in Ontario, Canada

Introduction: The complexity of navigating health and social care services is a common challenge to both providers and patients and their families. In the nineties, navigation programs arouse to assist cancer patients accessing services. Since then, those programs expanded to additional patient populations. Navigation programs can take various forms including virtual navigation. Virtual navigation in healthcare is a proactive process by which patients obtain information and support via internet resources to manage their illness demands.
 Approach: With a commitment to facilitate 24/7 access to its attributed population, Burlington Ontario Health Team (BOHT)-an integrated care network in Ontario- developed a mobile navigation app. Developing this app utilized experienced-based co-design approach. This approach took place via organizing a working group that included all stakeholders within the BOHT network of organizations and patient/caregiver partners. Over several months, the working group built potential personas of users, mapped their system navigation needs, created an inventory of navigation services within the network and designed the navigation app. Creation of the app was an iterative process including several testing and feedback loops to improve content and usability.
 Results: The first iteration of Burlington Navigation app was launched in Fall of 2021 accompanied by a comprehensive communication plan. The plan included digital signals at the hospital and primary care offices, social media posts and presentations to local providers including primary care physicians, community navigators. The first iteration focused on linking to health, social and community services offered by BOHT’s members and collaborators, and also services that were widely used in the community. Based on the feedback we received afterwards, the second iteration included links to provincial services. The third iteration includes capability to create a trusted account verified in the background by the same technology Interac uses. This will allow secure and seamless access to integrated services without a need for a separate username and password as well as access to the provincial patient portal
 Implications/highlights: Burlington Navigation app was the first community-based navigator app co-designed with patient partners, providers and community volunteers with lived experiences within the health and social care systems in Ontario. It resonated well with the users (providers and patients/caregivers) as local information became available at their fingertips. The success of the app allowed it to guide other OHTs on a similar digital navigator design journey. It also became the blueprint for a provincial solution for a multi-tenant navigator, which would allow multiple OHTs to showcase the local navigation information (based on geolocation) as well as provincial offerings.
 Conclusion: Sharing our journey co-developing the Burlington navigation app demonstrates that when local health integrated care networks utilize experienced-based co-design approaches to planning healthcare interventions, this has the potential to a) develop solutions that are well perceived by patients and providers and b) scale and spread these local solutions to larger-scale solutions that can improve the experiences of a wider spectrum of providers and patients.

Observation and Analysis of VLF Nocturnal Multimode Interference Phenomenon based on Waveguide Mode Theory

Very low frequency (VLF) signals are propagated between the ground-ionosphere. Multimode interference will cause the phase to show oscillatory changes with distance while propagating at night, leading to abnormalities in the received VLF signal. This study uses the VLF signal received in Qingdao City, Shandong Province, from the Russian Alpha navigation system to explore the multimode interference problem of VLF signal propagation. The characteristics of the effect of multimode interference phenomena on the phase are analyzed according to the variation of the phase of the VLF signal. However, the phase of VLF signals will also be affected by the X-ray and energetic particles that are released during the eruption of solar flares, therefore the two phenomena are studied in this work. It is concluded that the X-ray will not affect the phase of VLF signals at night, but the energetic particles will affect the phase change, and the influence of energetic particles should be excluded in the study of multimode interference phenomena. Using VLF signals for navigation positioning in degraded or unavailable GPS conditions is of great practical significance for VLF navigation systems as it can avoid the influence of multimode interference and improve positioning accuracy.

Robot-assisted navigation for percutaneous localization of peripheral pulmonary nodule: an in vivo swine study.

Robot-assisted surgery (RAS) systems have been developed but rarely applied to lung nodule localization. This study aimed to assess the feasibility and safety of using a robot-assisted navigation system in percutaneous lung nodule localization. A computed tomography (CT)-guided robot-assisted navigation system was used to localize the simulated peripheral nodule in the swine lung through fluorescent agent injection. After the localization, fluorescent thoracoscopic wedge resection was performed. The deviation between the target point and the needle tip was measured using a professional 3-dimensional (3D) distance measurement software. The primary outcome was the localization accuracy (deviation) of the localization. The secondary outcomes were the localization-related complication rate, the localization duration, and the success rate. A total of 4 pigs were enrolled, and 20 peripheral lung nodules were created and localized successfully. All nodules underwent subsequent wedge resection for verification. The mean deviation by measuring the 3D distance was 3.81 mm [standard deviation (SD): 1.29 mm, 95% confidence interval (CI): 2.936-4.536 mm]. The technical success rate for localization was 100%, and the mean localization time was 14.69 minutes (SD: 4.67 minutes). The complication rate was 5% (1/20), with 1 pneumothorax after localization, and no mortality occurred. This pilot animal study demonstrated the promising potential of the robot-assisted navigation technique in peripheral lung nodule localization, with high accuracy and feasibility. Further clinical trials are needed to validate its safety compared to traditional manual localization.

Consistency of the Troposphere Wet Delay From Water Vapor Radiometer and Co‐Located GPS Station

AbstractThe tropospheric delay acquired by the Global Navigation Position System (GPS) Precise Point Positioning (PPP) is continuous and steady, less affected by rainfall. The Water Vapor Radiometer (WVR) can provide real‐time meteorological parameters but is more sensitive to high‐frequency information in troposphere. To explore the use of WVR‐retrieved tropospheric delay and assist other geodetic techniques for atmospheric correction, the tropospheric delay from WVR and co‐located GPS at Shanghai, Beijing, Kunming, and Urumqi stations in China are compared. For the inconsistent values of WVR‐PPP zenith wet delay, the variations of the tropospheric delay from WVR and GPS before and after the rainfall were statistically analyzed. The results suggest that, for the rain rate ranging from 0.1 to 50 mm/hr, the impact of rainfall on WVR could last from 10 min before to 30 min after the rainfall. With filtering WVR data based on meteorological parameters and rain rate, the zenith wet delay between WVR and PPP at Shanghai shows good consistency, the root mean square (RMS) is 6.11 mm, correlation is 0.997, and the RMS in the other three stations ranges from 16.35 to 25.16 mm (correlation ranges in 0.794–0.951). The analysis indicates that the tropospheric delay of WVR is reliable to be applied to space geodetic techniques correction in real‐time with filtering to reduce the effect of rainfall, water vapor, and liquid water variability.

Review of the Monothematic Series of Publications Concerning Research on Statistical Distributions of Navigation Positioning System Errors

This review presents the main results of the author’s study, obtained as part of the post-doctoral (habilitation) dissertation entitled “Research on Statistical Distributions of Navigation Positioning System Errors”, which constitutes a series of five thematically linked scientific publications. The main scientific aim of this series is to answer the question of what statistical distributions follow the position errors of navigation systems, such as Differential Global Positioning System (DGPS), European Geostationary Navigation Overlay Service (EGNOS), Global Positioning System (GPS), and others. All of the positioning systems under study (Decca Navigator, DGPS, EGNOS, and GPS) are characterised by the Position Random Walk (PRW), which means that latitude and longitude errors do not appear randomly, being a feature of the normal distribution. The research showed that the Gaussian distribution is not an optimal distribution for the modelling of navigation positioning system errors. A higher fit to the 1D and 2D position errors was exhibited by such distributions as beta, gamma, and lognormal. Moreover, it was proven that the Twice the Distance Root Mean Square (2DRMS(2D)) measure, which assumes a priori normal distribution of position errors in relation to latitude and latitude, was smaller by 10–14% than the position error value from which 95% fixes were smaller (it is known as the R95(2D) measure).

Phased Array Radio Navigation System on UAVs: In-Flight Calibration

Global Navigation Satellite Systems (GNSS) has been the primary positioning solution for Unmanned Aerial Vehicles (UAVs) due to their worldwide coverage, high precision and lightweight receivers. However, GNSS is prone to electromagnetic interference and malicious assaults, including jamming or spoofing because of its low signal-to-noise ratio (SNR). To ensure the continuity and protection of UAV operations, using redundant navigation systems is essential. In recent years, the phased array radio system (PARS) has established itself as a local navigation solution. PARS is robust towards malicious assaults because of an much higher SNR than GNSS regarding directed and encrypted transmission. An essential factor of PARS is that the orientation of the radio antenna at a ground station needs to be precisely determined to obtain the correct positioning of UAVs. This paper presents a method for extending a previously proposed calibration algorithm to estimate the ground antenna orientation with an inertial navigation system (INS) aided by redundant positioning sensors (GNSS, PARS or barometer) using a multiplicative extended Kalman filter (MEKF) so that the calibration can be activated during flights whenever GNSS is available. In other words, the proposed navigation system is essentially an aided-INS which switches between two modes depending on the availability of GNSS: calibration and GNSS aiding mode when GNSS is available (Mode 1) and PARS and barometer aiding mode when GNSS is unavailable (Mode 2). Considering that the navigation system needs to include the effect of Earth’s curvature for a long-distance flight, PARS horizontal measurement and the barometer measurement were treated independently, and the navigation equations were propagated in Earth Centred Earth Fixed (ECEF) frame. The independent treatment of barometer measurement, and the propagation in ECEF frame were also beneficial when using multiple ground antennas to have a common reference point and reference frame. The proposed method was validated using data (Inertial Measurement Unit (IMU), GNSS, PARS, Pixhawk autopilot (including barometer) measurements) collected during a field test. In the validation, GNSS was made available at the middle of the flight and the calibration mode was activated for 200s. The proposed navigation system successfully estimated the precise orientation of multiple ground antennas and the navigation solutions were verified using GNSS and Pixhawk autopilot solutions as ground truth.

Autonomous ship navigation with an enhanced safety collision avoidance technique

The motion of an autonomous ship is different from that of ground and aerial robots due to its maneuvering and environmental constraints. As a result, many techniques have been introduced for autonomous ship path planning. This paper presents a novel technique for global and local navigation planning of autonomous ships under complex static and dynamic constraints. Our technique, termed safety-enhanced path planning (SPP), has been developed to avoid potential collisions with underwater obstacles near seaside areas. SPP pre-processes the map to preserve the shape of visible obstacles and mark a safety-outline around the shores. Subsequently, an offset safety line (OSL) is drawn about the original shore to protect the ship when passing close to threat-defined offshore areas. The global path is produced with an enhanced A* multi-directional algorithm, considering the kinematic constraint of the ship. To ensure optimal path quality, the global path is further refined with a smoothing filter to improve consistency and smoothness. Additionally, local navigation is introduced to help the autonomous ship avoid collisions with other obstacle ships. Local offset trajectories are produced with 4th and 5th degree polynomials along longitudinal and lateral coordinates in time t. Distance closest point approach (DCPA) is utilized for early obstacle prediction to help the ship maneuver in complex dynamic obstacle avoidance scenarios. The trajectory set is filtered with an efficient cost policy to obtain the best trajectory for dynamic collision avoidance. We conduct simulations in MATLAB and compared with other maritime path planning methods to verify the effectiveness of our approach.

Analysis of the precision of determination of aircraft coordinates using EGNOS+SDCM solution

This paper presents an algorithm for determining the precision parameter for aircraft position coordinates based on a combined GPS/EGNOS and GPS/SDCM solution. The proposed algorithm uses a weighted average model that com-bines a single GPS/EGNOS and GPS/SDCM position navigation solution to determine the resulting aircraft coordi-nates. The weighted mean model include the linear coefficients as a function of: the inverse of the number of tracked GPS satellites for which EGNOS and SDCM corrections have been generated, and the inverse of the geometric coeffi-cient of the PDOP (Position Dilution of Precision). The corrections between the single GPS/EGNOS and GPS/SDCM solution to the aircraft's resultant coordinates are then calculated on this basis. Finally, the standard deviation for the aircraft resultant BLh (B-Latitude, L-Longitude, h- ellipsoidal height) coordinates is calculated as a measure of preci-sion. The research experiment used recorded on-board GPS+SBAS data from two GNSS receivers mounted on a Dia-mond DA 20-C1 aircraft. The test flight was carried out on the Olsztyn-Suwaki-Olsztyn route. The calculations of aircraft position based on GPS/EGNOS and GPS/SDCM solution were performed in the RTKLIB v.2.4.3 program in the RTKPOST module. Next, aircraft resultant coordinates and standard deviations were computed in Scilab v.6.0.0 soft-ware package. Based on the tests performed, it was found that for the Trimble Alloy receiver, the standard deviation values for the ellipsoidal coordinates BLh of the aircraft do not exceed 1.77 m. However, for the Septentrio AsterRx2i receiver, the values of standard deviations for the aircraft's ellipsoidal BLh coordinates do not exceed 5.04 m. The use of linear coefficients as the inverse of the number of tracked GPS satellites with SBAS corrections in the GPS/EGNOS+GPS/SDCM positioning model resulted in a reduction in standard deviations of approximately 50-51% relative to the solution with linear coefficients calculated as the inverse of the PDOP parameter. In paper, the standard deviation was also obtained using arithmetic mean model. However the values of standard deviation from weighted mean model are lower than arithmetic mean model.

Issues of organizing vessels pilotage through the drawbridges spans in St. Petersburg

The topic of the work is an overview study of the current problem associated with the complexity of navigation of river vessels and river-sea-going vessels during their passage along the Neva River in the raised spans of St. Petersburg bridges. It is noted that when passing through the raised spans of St. Petersburg bridges in the induced state, such factor as the “surface dimension” is one of the main ones. It is emphasized that large-tonnage river and river-sea-going vessels cannot pass all the bridges of St. Petersburg when they are in the induced state, but since the bridges are drawn at night during navigation period, the height restriction is no longer so strict. Unfortunately, all bridges of St. Petersburg have only one draw span, so reverse navigation is organized through their raised spans in order, firstly, to avoid divergences of vessels in the sections between the bridges and, secondly, to enable the skipper to minimize manoeuvring when choosing the optimal path of entry into the raised span of the bridge. In addition, the attention is drawn to the fact that when entering the drawbridge span, the skipper must take into account many additional factors, including, for example, local navigation features, the actual hydro-meteorological situation and the current hydrological regime of the Neva River. It is noted in the study that the boatmaster should take into account such an important circumstance as the presence of a large number of pleasure craft used for sightseeing viewing of the process of vessel movement through the raised spans of bridges. Due to the fact that boatmasters of large-tonnage river vessels and river-sea-going vessels may experience significant difficulties in the process of organizing navigation safety when moving into the raised bridge spans on the Neva River section within the boundaries of St. Petersburg; mandatory pilotage, some features of the organization of which are considered in this work, has been established. Examples of accidents related to the procedure of bridges drawing that occurred within the boundaries of St. Petersburg and had serious consequences are analyzed. The amendments proposed to be made to the “Rules of movement and mooring of vessels in the Volga-Baltic basin of the inland waterways of the Russian Federation” in relation to the issue under consideration are considered.

Research on Multi-Sensor Data Fusion Positioning Method of Unmanned Ships Based on Threshold- and Hierarchical-Capacity Particle Filter

To improve the positioning accuracy of unmanned ships, a multi-sensor system including ZigBee, a Global Positioning System (GPS), and BeiDou Navigation Satellite System (BDS) is constructed, and an adaptive multi-sensor data fusion positioning method based on the threshold and hierarchical capacity particle filter (TCPF) is designed. First, the ZigBee-GPS/BDS multi-sensor measurement data is preprocessed to achieve a consistent space–time reference and transformed into the same coordinate system by projection. Then, the fault data is weighted and corrected through the consistency inspection of ZigBee-GPS/BDS multi-sensor positioning data, and the corresponding confidence factor is given according to the confidence distance of the positioning data; furthermore, the confidence factor is associated with stratified sampling. After that, the multi-sensor positioning data is filtered and denoised using a basic particle filter. Finally, a TCPF data fusion algorithm is designed, and the navigation positioning data of the unmanned ship is fused and filtered to obtain its positioning information. Numerical tests show that compared with other filtering algorithms, the mean square root error and standard deviation of the proposed TCPF algorithm decrease by an average of 25.0% and 28.0%, respectively, which verifies its high filtering accuracy and its advantages in suppressing particle degradation and avoiding sample scarcity. The experimental tests show that compared with other fusion algorithms, the proposed TCPF algorithm can not only realize the precise positioning during unmanned ship navigation, but also in the positioning and fault tolerance test, the average positioning error, root-mean-square error, and standard deviation of the former decrease by 36.0%, 38.0%, and 37.0%, respectively, and the corresponding performance indicators of the latter decrease by an average of 20.0%, 19.5%, and 17.5%, which verifies that it has the advantages of high data reliability and good filtering fault tolerance, and helps to improve the positioning accuracy of unmanned ships.

Local Navigation and Obstacle Avoidance for an Agricultural Tractor With Nonlinear Model Predictive Control

Local Navigation and Obstacle Avoidance for an Agricultural Tractor With Nonlinear Model Predictive Control

Satellite Interference Source Direction of Arrival (DOA) Estimation Based on Frequency Domain Covariance Matrix Reconstruction.

Direction of arrival (DOA) estimation is an effective method for detecting various active interference signals during the satellite navigation process. It can be utilized for both interference detection and anti-interference applications. This paper proposes a DOA estimation algorithm for satellite interference sources based on frequency domain covariance matrix reconstruction (FDCMR) to address various types of active interference that may occur in the satellite navigation positioning process. This algorithm can estimate the DOA of coherent signals from multiple frequency points under low signal-to-noise ratio (SNR) conditions. The signals received from the array are transformed from the time domain to the frequency domain using a fast Fourier transform (FFT). The data corresponding to the frequency point of the target signal is extracted from the signal in the frequency domain. The frequency domain covariance matrix of the received array signals is reconstructed by utilizing its covariance matrix property. The spatial spectrum search method is used for the final DOA estimation. Simulation experiments have shown that the proposed algorithm performs well in the DOA estimation under low SNR conditions and also resolves coherency. Moreover, the algorithm's effectiveness is verified through comparison with three other algorithms. Finally, the algorithm's applicability is validated through simulations of various interference scenarios.

Intelligent Fault Diagnosis Methods for Hydraulic Piston Pumps: A Review

As the modern industry rapidly advances toward digitalization, networking, and intelligence, intelligent fault diagnosis technology has become a necessary measure to ensure the safe and stable operation of mechanical equipment and effectively avoid major disaster accidents and huge economic losses caused by mechanical equipment failure. As the “power heart” of hydraulic transmission systems, hydraulic piston pumps (HPPs) occupy an important position in aerospace, navigation, national defense, industry, and many other high-tech fields due to their high-rated pressure, compact structure, high efficiency, convenient flow regulation, and other advantages. Faults in HPPs can create serious hazards. In this paper, the research on fault recognition technology for HPPs is reviewed. Firstly, the existing fault diagnosis methods are described, and the typical fault types and mechanisms of HPPs are introduced. Then, the current research achievements regarding fault diagnosis in HPPs are summarized based on three aspects: the traditional intelligent fault diagnosis method, the modern intelligent fault diagnosis method, and the combined intelligent fault diagnosis method. Finally, the future development trend of fault identification methods for HPPs is discussed and summarized. This work provides a reference for developing intelligent, efficient, and accurate fault recognition methods for HPPs. Moreover, this review will help to increase the safety, stability, and reliability of HPPs and promote the implementation of hydraulic transmission technology in the era of intelligent operation and maintenance.

A Depth-Based Hybrid Approach for Safe Flight Corridor Generation in Memoryless Planning.

This paper presents a depth-based hybrid method to generate safe flight corridors for a memoryless local navigation planner. It is first proposed to use raw depth images as inputs in the learning-based object-detection engine with no requirement for map fusion. We then employ an object-detection network to directly predict the base of polyhedral safe corridors in a new raw depth image. Furthermore, we apply a verification procedure to eliminate any false predictions so that the resulting collision-free corridors are guaranteed. More importantly, the proposed mechanism helps produce separate safe corridors with minimal overlap that are suitable to be used as space boundaries for path planning. The average intersection of union (IoU) of corridors obtained by the proposed algorithm is less than 2%. To evaluate the effectiveness of our method, we incorporated it into a memoryless planner with a straight-line path-planning algorithm. We then tested the entire system in both synthetic and real-world obstacle-dense environments. The obtained results with very high success rates demonstrate that the proposed approach is highly capable of producing safe corridors for memoryless local planning.

Cross-Modal Images Matching Based Enhancement to MEMS INS for UAV Navigation in GNSS Denied Environments

A new cross-modal image matching method is proposed to solve the problem that unmanned aerial vehicles (UAVs) are difficult to navigate in GPS-free environment and night environment. In this algorithm, infrared image or visible image is matched with satellite visible image. The matching process is divided into two steps, namely, coarse matching and fine alignment. Based on the dense structure features, the coarse matching algorithm can realize the position update above 10 Hz with a small amount of computation. Based on the end-to-end matching network, the fine alignment algorithm can align the multi-sensor image with the satellite image under the condition of interference. In order to obtain the position and heading information with higher accuracy, the fusion of the information after visual matching with the inertial information can restrain the divergence of the inertial navigation position error. The experiment shows that it has the advantages of strong anti-interference ability, strong reliability, and low requirements on hardware, which is expected to be applied in the field of unmanned navigation.