125 results about "Navigation error" patented technology

The invention provides an oral implant navigation method and system and a storage medium, after an optical locator is fixedly arranged on an implant mobile phone, three-dimensional data of a rotating shaft of the implant mobile phone, the tail end of the rotating shaft and a spherical drill on an optical three-dimensional coordinate system of the optical locator are obtained, and a registration pit is used as a medium to obtain a three-dimensional coordinate system of the implant mobile phone; and positioning three-dimensional data of the three-dimensional coordinate system in the optical three-dimensional coordinate system, registering the three-dimensional data of the pits on the CT three-dimensional coordinate system to complete registration, calculating the pose of the tip of the drill point and the pose of the ideal path under the positioning three-dimensional coordinate system, and performing real-time navigation on the planted mobile phone according to the difference between the tip of the drill point and the ideal path. An optical positioning instrument is fixedly arranged on the planting mobile phone, and while the planting mobile phone is used for drilling operation, image data of the optical identification points are collected through the optical positioning instrument for real-time navigation; the optical positioning instrument and the planting mobile phone are integrally connected, so that the process of positioning the planting mobile phone in real time can be omitted, and navigation errors are effectively reduced.

The invention discloses a hinged wheel type pipeline robot positioning method based on multi-sensor fusion ESKF, which takes the ESKF as a core, predicts the nominal state of an IMU through a double-subsample INS mechanical arrangement method, introduces an adaptive slip detection method based on IMU kinematics consistency constraint to perform reliability verification on multi-encoder observation, and finally determines the position of the hinged wheel type pipeline robot. Speed observation fusion is realized; meanwhile, heading updating of the magnetometer is triggered through magnetic field stability detection, and long-term drift is restrained; a pseudo measurement constraint model is established based on pipeline environment characteristics, and accumulative errors are systematically inhibited; and after feedback compensation is carried out on IMU errors and navigation errors through ESKF measurement updating, position, speed and attitude navigation data are output in real time. And finally, performing global posterior optimization on the real-time filtering trajectory by adopting an RTS reverse smoothing algorithm, thereby effectively solving the problems of low positioning precision and insufficient adaptability of a multi-section hinge wheel type pipeline robot structure in a complex underground pipe network.

The invention discloses an inertial navigation error compensation method and system based on gravity assistance, and belongs to the field of navigation. The inertial navigation error compensation method is suitable for long-time indoor inspection of the robot. Firstly, channel state information, odometer data and inertial measurement data of a robot are obtained; calculating an initial attitude through angular velocity integration, and calibrating a pitch angle and a roll angle by using the separated gravity vector; calculating a motion increment based on odometer data, and performing coordinate conversion in combination with the calibration attitude to obtain navigation position information; inputting the channel state information into a neural network to obtain a channel fingerprint, and matching target position information; and finally, calculating the cross covariance between the navigation position and the target position to obtain a state correction value, and compensating the navigation position and course angle error. According to the invention, when inertial navigation error compensation is carried out on the robot for long-time indoor inspection, the compensation accuracy and effect can be improved.

The invention discloses a vision and inertial navigation integrated navigation method, system and equipment in a weak vision environment and a medium, and belongs to the technical field of navigation, by fusing an inertial measurement unit and landmark focal plane projection data, the navigation precision of the system under the adverse conditions of low texture, dynamic shielding and the like is remarkably improved, and the navigation continuity can be maintained; according to the method, an indirect Kalman filter is used for carrying out feedback correction on initial navigation parameters, noise interference and inertial navigation accumulative errors are effectively inhibited, navigation errors are remarkably reduced for state estimation, and the robustness and adaptability of the system are enhanced; the method does not depend on complete visual resolving, landmark projection coordinates are directly used, dependence on visual information integrity is reduced, and the system can stably operate even if only a small number of landmarks or a single landmark is visible.

The invention relates to the technical field of robot navigation, and discloses a visual positioning method, self-moving equipment and a storage medium, and the method comprises the steps: obtaining a plurality of frames of environment images containing a time sequence relation; analyzing the multi-frame environment image to obtain an anomaly recognition result in the environment image; extracting effective features based on the multi-frame environment image to obtain a first effective feature set; screening the first effective feature set according to an anomaly recognition result, and removing false features corresponding to the image anomaly to obtain a second effective feature set after the anomaly is removed; and calculating pose information of the self-moving device based on the second effective feature set. According to the technical scheme, the accuracy and robustness of visual positioning are improved, and navigation errors caused by image abnormity are reduced.

The invention discloses a waypoint prediction method fusing instruction landmark features in visual language navigation, and belongs to the crossing field of artificial intelligence and computer vision. The method is realized through the following steps: firstly, extracting landmarks and co-occurrence landmarks thereof from a natural language instruction by utilizing a large language model, and generating a candidate landmark sequence; then, the occurrence probability of the candidate landmarks in actual observation is calculated based on a visual large model CLIP, and noise interference is dynamically corrected and suppressed through a learnable co-occurrence scoring module; secondly, fusing the corrected landmark features with the depth visual features, inputting a double-layer Transform model to model a spatial relationship, generating a waypoint probability heat map, and outputting adjacent waypoints through non-maximum suppression (NMS); and finally, topological mapping is carried out on the predicted waypoints, an optimal path is obtained through cross-modal path planning, and an intelligent agent is guided to execute low-level actions. The method does not need to depend on a predefined environment map or manually annotate data, navigation errors in a continuous environment are remarkably reduced, the generalization ability of unseen scenes is improved, and the method is suitable for open world navigation scenes such as robot navigation and automatic driving.

The invention relates to the technical field of electric power facility monitoring, and discloses an electric power line detection system based on a three-dimensional inertial gyroscope and deep learning, which comprises a data acquisition module, a segmented preprocessing module, a trajectory resolving module, a trajectory correction module, a deviation analysis module and a risk early warning module. According to the application, the electromagnetic shielding and common-mode noise suppression technology is adopted to overcome high-voltage electromagnetic field interference, and the data acquisition quality is ensured; precise adaptation of different line features is realized through segmented adaptive preprocessing; inertial navigation error accumulation is effectively inhibited by utilizing topological constraint and multi-source data fusion; the problem of deviation identification under the small sample condition is solved by combining an attention mechanism and transfer learning; and finally, intelligent risk assessment and early warning are realized through deep reinforcement learning, so that whole-process intelligent processing from original data to risk assessment is realized, and the precision and efficiency of power line detection are improved.

The invention provides an intelligent hospital guide system and method based on AR vision and voice navigation. The intelligent hospital guide system comprises a user interaction layer, a technical support layer, a data and background layer, a third-party service layer and a hardware dependence layer. According to the intelligent hospital guide system based on AR vision and voice navigation, accurate navigation is achieved, a barrier-free road is guided, through the advanced AR vision navigation technology, the APP provides an accurate and errorless navigation path for a patient, the possibility of navigation errors is greatly reduced, virtuality and reality are seamlessly fused, and the intelligent hospital guide system based on AR vision and voice navigation has the advantages of being high in practicability and the like. The patient can walk on a familiar map in a hospital, and each step is full of confidence; the voice navigation function brings unprecedented convenience to the user, and especially for the visual impairment, the old or the users with inconvenience in hands, the service is as an intimate guide to lead the visual impairment, the old or the users with inconvenience in hands to easily shuttle to all corners of a hospital and enjoy barrier-free medical experience.

The invention discloses a self-adaptive integrated navigation method and system based on satellite differential signals, and belongs to the field of integrated navigation, and the method comprises the following steps: carrying out state prediction based on the output of an inertial navigation system; a deviation function is established through sliding window fitting, and effectiveness evaluation and preventive correction are carried out on differential satellite navigation system signals; dynamically adjusting a measurement noise matrix according to the positioning mode and performing residual error verification; carrying out measurement updating by utilizing the deviation passing the verification to obtain an estimated value containing the error of the inertial device so as to carry out closed-loop feedback correction on navigation parameters; and when the satellite signal fails, compensating the inertial navigation system by using the device error parameter in the estimated value and realizing pure inertial recursion. According to the method, the data quality can be improved from the source, the self-adaptive robustness of the system in a complex environment is enhanced, inertial navigation error divergence is continuously inhibited, and the navigation endurance precision under the extreme condition of satellite signal failure is guaranteed.

The invention discloses an inertial navigation error magnitude prediction method based on a neural network, and belongs to the technical field of inertial navigation. The method comprises the following steps: constructing a feedforward BP neural network introducing time input, taking a standard deviation of an inertial navigation error factor and a carrier motion state as input, and taking an east, north and day three-direction position error standard deviation as output; adopting a Monte Carlo method to generate a high-fidelity training data set based on the plurality of reference trajectories; and a Levenberg-Marquardt algorithm is used to train the network, and accurate fitting of a complex error relation is realized. According to the method, the inertial navigation position error magnitude can be rapidly predicted on line, key error information is provided for adaptive Kalman filtering, and the method has high engineering application value.

The application provides a carrier motion excitation micro-inertial navigation error parameter identification and prediction method, which effectively combines micro-inertial navigation use data and calibration data, compensates device errors according to use environment and motion conditions, fully utilizes historical data, improves micro-inertial navigation key error parameter compensation precision, and further improves micro-inertial navigation performance; meanwhile, the application also introduces the influence of motion excitation on error parameter compensation precision, avoids data pollution of calibration results caused by failure to excite errors; finally, the learning and prediction method of micro-inertial navigation error parameter change trend provided by the application can reduce device errors caused by use life growth, and prolong the service life of the micro-inertial navigation.

The application provides a spacecraft autonomous navigation method and electronic equipment. The spacecraft autonomous navigation method comprises the following steps: determining technical indexes of an optical sensor according to navigation requirements, and determining a configuration of the optical sensor according to orbit information of the spacecraft; collecting a star map by using the optical sensor with the determined technical indexes and configuration, processing the star map, identifying a refraction star and extracting a refraction angle; and using a Kalman filtering algorithm to perform information fusion on information output by an inertial navigation system and a refraction apparent height calculated based on the refraction angle, so as to correct navigation errors and obtain corrected navigation information. The application corrects drift errors of the inertial navigation by astronomical navigation, maintains continuous navigation information by using the inertial navigation when the astronomical system is unavailable, and achieves the purpose of improving navigation accuracy.

The application provides a space domain deviation processing device, method and storage medium, and belongs to the technical field of radio positioning and navigation. The space domain deviation processing device comprises: an acquisition unit that acquires inertial measurement data and space domain observation data; a modeling unit that constructs an augmented error state vector comprising a carrier navigation error state and a space domain deviation state; a reference construction unit that recursively constructs a nominal pose of the carrier based on the inertial measurement data and updates an error covariance matrix; a residual calculation unit that constructs a residual based on the nominal pose, the space domain deviation state and an observation model; and an updating unit that corrects and updates the space domain deviation state according to the residual and the error covariance matrix. The space domain deviation processing device provided by the application can reduce the influence of the space domain deviation state on the carrier pose state, reduce the navigation drift problem caused by antenna installation deviation or multipath interference, and improve the positioning and pose stability.

The invention discloses an airborne bistatic radar platform error compensation and target positioning method and system. The method comprises the following steps: constructing a measurement model for a bistatic radar system; the measurement model comprises a platform position motion model, a target position motion model, an observation equation of a platform to a target and a navigation error model of the platform; based on the measurement model, performing linear fitting on each platform position measurement and target position measurement by using a linear fitting model, estimating navigation error parameters of each platform according to fitting results, and correcting platform motion parameters according to estimated values of the navigation error parameters; and based on the corrected platform motion parameters, constructing a linearized target positioning model in combination with multi-platform observation data, and estimating the motion parameters of the target by using a weighted least square method to realize target positioning. Under the condition that no navigation source exists, the positioning precision of the airborne platform is improved, and then the positioning precision of the bistatic airborne radar on the non-cooperative target is improved.

This invention discloses an adaptive inertial navigation solution method and system based on motion feature recognition, comprising: extracting multidimensional features reflecting the motion state of the carrier based on angular velocity and specific force data collected by the inertial measurement unit, and constructing a feature matrix; performing dimensionality reduction processing on the feature matrix to obtain low-dimensional feature vectors; performing cluster analysis based on a clustering algorithm that initializes cluster centers using prior samples to identify the motion state of the carrier; and adaptively selecting an appropriate combined navigation filtering strategy for navigation solution. This invention effectively suppresses the accumulation of inertial navigation errors, improving the autonomous navigation accuracy and long-term stability of the system in scenarios of satellite signal rejection or visual failure; it can finely distinguish different motion modes such as hovering, uniform motion, and transitional states, avoiding the shortcomings of traditional threshold methods that are susceptible to noise interference and have poor adaptability; by introducing continuous frame mode voting and physical anti-jump mechanisms, it further eliminates single-frame misjudgments, ensuring the continuity and robustness of state recognition.

The invention relates to a biaxial rotation inertial navigation error modulation parameter selection method based on an error propagation equation, and belongs to the technical field of inertial navigation, and the method comprises the following steps: S1, constructing a biaxial rotation inertial navigation error propagation equation considering an error modulation effect; s2, setting a transposition sequence of the biaxial rotation inertial navigation; s3, based on the error propagation equation constructed in the step S1 and the transposition sequence set in the step S2, obtaining navigation errors at different rotation speeds and navigation errors at different rotation stopping time; and S4, determining the optimal rotation speed and rotation stop time based on the navigation errors at different rotation speeds and the navigation errors at different rotation stop time obtained in the step S3. The method improves the navigation precision of double-shaft rotation inertial navigation, is simple to operate, low in time consumption, low in cost, good in selection effect, high in navigation precision and good in practicability, and solves the problems of long time consumption, high cost, poor selection effect and low navigation precision of the existing empirical method.

The invention relates to the technical field of route navigation, in particular to an underground space AR (Augmented Reality) navigation system based on a visual identification feature point technology, which comprises a spatial modeling and data processing module, an identification system management module, a client application module, a real-time positioning module, a navigation engine module and a dynamic data management module. According to the method, aiming at underground multi-layer space design, a centimeter-level three-dimensional base drawing is pre-constructed by utilizing a completed BIM / CAD drawing, a three-dimensional anchor point is formed through an anti-shielding code mark pasted on the surface of a fixed structure such as a beam column, accurate distinguishing and positioning between an upper floor and a lower floor can be realized under a complete off-line condition, and when traditional GPS and Bluetooth signals fail, the positioning accuracy of the upper floor and the lower floor can be improved. The system can still complete cross or triangular positioning by visually identifying the anchor points, and the problem of navigation errors caused by unclear upstairs and downstairs division is solved.

The present application relates to the technical field of inertial navigation, and provides an inertial navigation error correction method, system and device based on reverse sequence navigation solution, which comprises the following steps: recording original data measured by an inertial navigation system from starting to the end of alignment and into navigation time; recording gyro drift and platform initial misalignment angle estimated by an alignment filter at the end of alignment and into navigation time; performing navigation solution on the original data based on time reverse sequence, estimating gyro drift error according to reverse sequence navigation result, and performing secondary compensation on gyro drift and platform initial misalignment angle error; and performing navigation solution based on compensated platform misalignment angle and gyro drift from navigation time. The present application performs reverse sequence navigation solution based on alignment parameters and data recorded in the alignment stage after the end of alignment, and realizes secondary estimation and compensation of drift and misalignment angle error after the alignment stage based on the solution result, so as to obtain higher navigation precision.

The invention provides a spacecraft autonomous navigation method and electronic equipment. The autonomous navigation method for the spacecraft comprises the following steps: determining a technical index of an optical sensor according to a navigation requirement, and determining a configuration of the optical sensor according to orbit information of the spacecraft; acquiring a star map by using an optical sensor with determined technical indexes and configuration, processing the star map, identifying a refraction star and extracting a refraction angle; and carrying out information fusion on the information output by the inertial navigation system and the refraction apparent height calculated based on the refraction angle by using a Kalman filtering algorithm so as to correct the navigation error and obtain the corrected navigation information. The drifting error of the inertial navigation is corrected through the astronomical navigation, and the navigation information is kept continuous through the inertial navigation when the astronomical system is unavailable, so that the purpose of improving the navigation precision is achieved.

The invention discloses a GPS (Global Positioning System) and inertial navigation fused high-precision navigation method, aiming at the problems that a GPS signal is easily shielded and interfered and an inertial navigation error is accumulated along with time, high-precision navigation is realized through data preprocessing, a self-adaptive fusion algorithm, GPS signal interruption processing and fusion result optimization. In the data preprocessing, multi-path effect detection and correction are performed on GPS data, and zero offset error compensation is performed on inertial navigation data; the adaptive fusion algorithm constructs a model based on a fuzzy logic system, and updates a fusion weight in real time; when a GPS signal is interrupted, map matching is adopted to assist navigation, and the prediction model is utilized to compensate an inertial navigation error; and a fusion result is subjected to wavelet filtering and smoothing processing, and the accuracy is ensured by using consistency check. The method can effectively overcome the limitation of independent use of GPS and inertial navigation, realizes high-precision, continuous and reliable navigation in a complex environment, and improves the adaptability and stability of a navigation system.

The present invention discloses a visually assisted gait feature constrained pedestrian navigation method, which comprises the following steps: firstly, using the data collected by the inertial measurement unit to analyze the gait characteristics of the pedestrian and calculate the zero-speed interval; then, calibrating the inertial measurement unit and the camera to obtain corresponding internal and external parameters, solving the position and attitude data of the six-degree-of-freedom of the visual inertial odometer, and obtaining the relative posture information of the pedestrian's movement; then adopting the strapdown inertial navigation calculation method to perform initial alignment and inertial navigation solution to obtain the pedestrian's instantaneous attitude, speed and position information; finally, establishing a Kalman filter model, using the speed difference and angular velocity difference in the zero-speed interval, the attitude error and position error when the visual signal is valid as observation quantities for measurement and update; using the current corrected state quantity as the initial quantity for the next inertial navigation solution, and repeating the navigation correction process. The present invention can constrain the divergence of navigation errors in an environment where GNSS signals fail, and improve the accuracy of pedestrian navigation positioning.

The invention discloses a parking lot mapping method, device and equipment and a storage medium, relates to the technical field of vehicle positioning, and discloses a parking lot mapping method comprising the following steps: initializing a parking lot map; obtaining a parking lot scene type; determining a target mapping strategy according to the parking lot scene type; determining a semantic element inter-frame error, a visual feature inter-frame error and an integrated navigation error according to the vehicle pose, the integrated navigation pose, the semantic element information and the visual feature information; and optimizing the parking lot map according to at least two of the semantic element inter-frame error, the visual feature inter-frame error and the combined navigation error through the target mapping strategy so as to complete parking lot mapping. According to the scheme, the mapping precision and stability under the full-parking-lot scene type can be improved.

The invention relates to the technical field of navigation, in particular to a mine monorail crane navigation method and system based on an odometer and inertial navigation. The method comprises the steps that the clamping force of a monorail crane driving wheel and the pulse number of an encoder are collected; based on a preset nonlinear relation model between the clamping force of the monorail crane driving wheel and the radial variable of the tire, obtaining the radial variable corresponding to the clamping force; determining the actual distance of the speedometer according to the radial variable and the encoder pulse number; calibrating the odometer measurement error based on the actual distance; after calibration is completed, establishing a strapdown inertial navigation / dead reckoning combined positioning model according to strapdown inertial navigation errors and dead reckoning errors; based on the combined positioning model, performing optimal estimation by using Kalman filtering; and performing feedback correction on inertial navigation error parameters according to an estimation result. The navigation precision of the mining monorail crane can be improved.

The invention discloses an inertial navigation error compensation method and system, and the method comprises the steps: calculating the angular accelerations of a carrier at different moments by using the angular velocity of the carrier and combining the accelerations measured by a plurality of accelerometers; then, the length of a lever arm is calculated according to the angular accelerations at different moments, and error estimation is carried out based on the length of the lever arm, so that the lever arm effect acceleration error of the main accelerometer is obtained; and finally, correcting the acceleration output by the main accelerometer according to the calculated lever arm effect acceleration error. Therefore, error compensation is carried out on the acceleration to reduce the adverse effect of the lever arm effect on the acceleration in inertial navigation, so that the positioning precision of the carrier can be effectively improved, and the method is very suitable for large-scale application and popularization in the technical field of inertial navigation.

The invention provides a BDS / INS navigation method and device based on innovation differential fault detection, and belongs to the technical field of navigation positioning. Determining a BDS pseudo-range measurement predicted value of the visual satellite based on the BDS ephemeris; calculating pseudo-range information according to the BDS pseudo-range measurement predicted value and pseudo-range measurement, and forming a current information set; the current innovation set and the historical preferred pseudo-range innovation set form a dynamic innovation data set; performing pairwise difference on pseudo-range information in the current information set and the dynamic information data set, and calculating information difference statistics of the N visual satellites based on a difference value; and then fault detection is carried out through iteration, and unavailable pseudo-range information is eliminated by comparing the information difference statistics with a fault detection threshold value in each iteration. And calculating a weight based on the available pseudo-range information, and carrying out Kalman filtering measurement updating to obtain navigation error state estimation. By using the method, the fault detection failure rate under the complex environment interference condition and the system error accumulation condition can be reduced.

The invention provides an inertial navigation error correction method and device based on photoelectric equipment image target detection, and belongs to the technical field of photoelectricity, and the method comprises the following steps: obtaining a photoelectric image of a to-be-detected target based on a pre-correction attitude angle of photoelectric equipment; performing target detection on the photoelectric image to obtain a target deviation angle; obtaining a horizontal coordinate system deviation angle based on the target deviation angle and the image rotation angle; obtaining an inertial navigation correction angle of the photoelectric equipment based on the horizontal coordinate system deviation angle and the tracking turntable direction; and performing inertial navigation error correction on the photoelectric equipment based on the inertial navigation correction angle. According to the inertial navigation error correction method and device based on photoelectric equipment image target detection, the inertial navigation error can be effectively reduced, and the pointing precision of photoelectric equipment is improved.

The application provides a neural network assisted vehicle adaptive autonomous navigation method, which comprises the following steps: designing an improved LSTM model for multi-parameter parallel prediction; collecting inertial measurement unit data and performing inertial navigation calculation; performing inertial / satellite integrated navigation calculation when satellite navigation is effective; training the designed parallel LSTM model based on the integrated navigation result; predicting vehicle speed and attitude information based on the trained machine learning model when satellite navigation is ineffective; and using variational Bayes based on the prediction result of the machine learning model to perform adaptive integrated navigation when satellite navigation is ineffective. The application overcomes the problem of insufficient cumulative accuracy of vehicle navigation error when only relying on inertial navigation without reference information, and can realize full autonomous and high-precision navigation and positioning of the vehicle, which has important practical application value.

The invention provides an adaptive collaborative navigation networking method and system based on a BP network. The method comprises the following steps: S1, generating a training data set based on a plurality of reference trajectories of nodes, and predicting the inertial navigation error magnitude of each node; s2, determining the number of aircraft cluster network nodes, measuring the relative distance between the nodes through a data link, and setting collaborative networking starting conditions based on the predicted inertial navigation error magnitude, the relative distance between the nodes and the calculated GDOP value; s3, making an adaptive collaborative networking strategy according to the predicted inertial navigation error magnitude and GDOP value of each node after a starting condition is met; and S4, constructing a rank depletion constraint Kalman filter according to the inertial navigation error distribution of each node, and carrying out optimal correction on the navigation information of the screened nodes. According to the method, the real-time optimal configuration of the collaborative networking formation is effectively ensured, the divergence of the pure inertial navigation error of each node is inhibited, and the real-time optimal estimation of the navigation information of each node in the cluster network is ensured.

The application discloses a heterogeneous flight cluster inertial navigation error cooperative correction method based on pseudo observation, which is composed of multiple unmanned aerial vehicles (UAVs) and the UAVs observe each other, and comprises the following steps: S1, acquiring inertial navigation positions of the UAVs at a current time and inertial navigation position estimation noises; S2, selecting a reference anchor point, and obtaining relative distance observation, relative azimuth observation and relative pitch angle observation among the UAVs in the cluster; S3, establishing an observation equation of the heterogeneous cluster UAVs according to the observation data obtained in the step S2; S4, constructing a pseudo observation equation according to whether the observation equation is sufficient; S5, classifying according to the rank of an observation matrix, and solving the observation equation; and S6, updating the inertial navigation position, attitude and speed of each UAV. The inertial navigation position information after correction is combined with the inertial navigation information to correct and update the navigation position, attitude and speed, and better overall positioning precision of the cluster can be obtained when the available observation quantity is insufficient.

The application relates to a Lie group strapdown inertial navigation error model based on a carrier system quaternion attitude error, which comprises that the quaternion attitude error can be divided into a navigation system quaternion attitude error and a carrier system quaternion attitude error, the application first deduces an attitude error model based on the carrier system quaternion, then on the basis, a Lie group strapdown inertial navigation error model based on the carrier system quaternion attitude error is proposed and deduced, the model has obvious advantages in the aspects of combined navigation positioning precision, error convergence speed and filter robustness, and the advantages are more prominent especially under the condition of large misalignment angle. Through experiment comparison of the advantages and disadvantages of four models, the application improves the deficiency of the existing literature on the combined navigation model under the condition of large misalignment angle, and the model can complete high-precision nonlinear combined navigation in a short time under the condition of large misalignment, and meets the requirement of high-precision combined navigation.