Navigation Method and Application of Satellite, Inertial Navigation, Spectrum Map, and Magnetometer Combination

Abstract

The present invention provides a navigation method combining satellite, inertial navigation, spectral map, and magnetometer. The method includes: acquiring sensor measurement data of a mobile intelligent platform; using the sensor measurement data to provide a high-precision positioning result in the case where satellite navigation is observable through satellite navigation and inertial navigation combined navigation; using inertial navigation extrapolation to provide inertial navigation positioning information when satellite navigation is unobservable; using magnetometer assistance to provide azimuth information when satellite navigation is unobservable; and providing navigation positioning information when satellite navigation is unobservable through spectral map matching positioning based on SIR particle filtering to prevent the accumulation of inertial navigation and magnetometer errors. By comprehensively applying satellite navigation, inertial navigation, spectral map, and magnetometer, the present invention solves the problem of the accumulation of inertial navigation and magnetometer errors caused by the unobservability of satellite navigation, and can be applied to high-precision navigation positioning of mobile intelligent platforms such as mobile phones or robots.

Description

Technical Field

[0001] The present invention belongs to the field of navigation technology, and in particular relates to a navigation method combining a satellite, an inertial navigation system, a spectrum map and a magnetometer. Background Art

[0002] With the continuous development of navigation technology, the limitations of single navigation systems (such as GNSS, INS, magnetometers, spectrum maps, etc.) have gradually emerged. For example, the global navigation satellite system (GNSS) can provide high-precision positioning information in an open environment, but in complex environments (such as urban high-rise buildings, tunnels, indoors, etc.), satellite signals are easily blocked or interfered with, resulting in reduced positioning accuracy or even inability to locate. Inertial navigation technology (INS) has the characteristics of strong autonomy and high short-term accuracy, but its errors will accumulate over time, resulting in poor long-term navigation accuracy; among them, micro-inertial navigation technology, based on the micro-inertial measurement unit (MIMU, Micro Inertial Measurement Unit) to achieve the measurement and positioning of the acceleration and angular velocity of the carrier platform, has the characteristics of lightweight, low cost, short time and high integration, but the accuracy is lower and needs to be compensated by calibration and filtering algorithms. Although the magnetometer can provide geomagnetic field information, it is easily interfered with in complex environments and produces errors, which requires calibration. In addition, navigation methods based on spectrum maps (Radio Map) are widely used, such as fingerprint positioning systems based on 5G, FM, Wifi and other signals. Although spectrum mapping technology can provide auxiliary positioning information through radio spectrum scenarios, its accuracy and reliability still need to be further improved.

[0003] In order to overcome the shortcomings of a single navigation system, by partially integrating multiple navigation technologies, the advantages of each system can be fully utilized, thereby improving the overall performance of the navigation system. However, there are still some problems in the existing technology for partial integration of multiple navigation technologies. For example, the fusion system of GNSS and INS may still be affected by the multipath effect in a complex environment; the calibration process of the magnetometer is complicated, and it is difficult to maintain high accuracy in a dynamic platform environment; the construction and update of the spectrum map requires a lot of computing resources, and the accuracy is greatly affected by environmental changes. Therefore, how to solve the problems of insufficient accuracy, error accumulation and poor environmental adaptability of a single sensor or partial combined navigation system in a complex environment is still a technical problem that needs to be solved in the field of navigation.

[0004] In addition, in an outdoor environment, it is extremely important to ensure the reliability of the navigation system of mobile intelligent devices (such as mobile phones, drones, or robots, etc.). The most commonly used navigation system is a combined navigation system of satellites, micro-inertial navigation, and magnetometers. Due to the lack of line-of-sight conditions between users and navigation satellites, when switching between indoor and outdoor environments, satellite signals are easily blocked. Relying solely on GNSS cannot provide reliable positioning estimates, which will cause error divergence of micro-inertial navigation or magnetometers and cannot provide accurate navigation and positioning services for seamless connection between indoor and outdoor environments. Summary of the Invention

[0005] To solve the above problems existing in the prior art, the present invention proposes a navigation method combining satellites, inertial navigation, spectrum maps, and magnetometers. By comprehensively applying various navigation technical means including satellites, inertial navigation, spectrum maps, and magnetometers, it solves the problem of error accumulation of micro-inertial navigation and magnetometers caused by satellite navigation rejection, effectively improves the navigation and positioning accuracy of the mobile intelligent platform equipped with the above, and further meets the seamless connection navigation and positioning requirements in occluded environments.

[0006] A navigation method combining satellites, inertial navigation, spectrum maps, and magnetometers includes:

[0007] Step 110, obtaining sensor measurement data of the mobile intelligent platform in real time and storing it in a data file; the sensor measurement data at least includes GNSS measurement information, inertial navigation measurement data, signal strength data, spectrum maps, and magnetometer measurement data;

[0008] Step 120, sampling the sensor measurement data from the data file and marking the sensor measurement data at each sampling time point with an epoch;

[0009] Step 130, performing data management and inertial navigation extrapolation on the inertial navigation measurement data to obtain an inertial navigation extrapolation result; the inertial navigation extrapolation result includes inertial navigation errors;

[0010] Step 140, determining the observability of navigation satellites based on the GNSS measurement information of the current epoch; if the navigation satellites are observable, using the inertial navigation extrapolation result and GNSS-inertial navigation combined navigation to obtain a combined navigation and positioning result, and re-executing Step 140 for the next epoch; if the navigation satellites are unobservable, execute Step 150;

[0011] Step 150, performing direction angle calculation and inertial navigation measurement data verification and correction on the magnetometer measurement data to obtain a reliable attitude result;

[0012] Step 160, after synchronizing the signal strength data and the spectrum map data, combining the inertial navigation extrapolation result and the reliable attitude result, and obtaining a spectrum map navigation positioning result through spectrum map matching positioning based on SIR particle filtering as the integrated navigation positioning result;

[0013] Step 170, using the spectrum map navigation positioning result to correct the inertial navigation error of the inertial navigation extrapolation result. After clearing the inertial navigation error state, re - execute Step 140 for the next epoch until all epochs are traversed, and output and save the integrated navigation positioning result.

[0014] In addition, the present invention also proposes an application of the foregoing navigation method combining satellite, inertial navigation, spectrum map, and magnetometer in a 5G mobile phone to achieve integrated navigation positioning of the 5G mobile phone. The inertial navigation adopts a micro - inertial navigation mode based on MIMU. The method includes:

[0015] Step 210, real - time obtain the sensor measurement data loaded on the 5G mobile phone and store it in a data file; the sensor measurement data at least includes GNSS measurement information, inertial navigation measurement data, signal strength data, spectrum map, and magnetometer measurement data; a GNSS and MIMU integrated navigation module, an inertial navigation extrapolation module, a spectrum map matching positioning module based on SIR particle filtering, a magnetometer assistance module, and a system error estimation module are installed on the 5G mobile phone;

[0016] Step 220, sample the sensor measurement data from the data file and mark the sensor measurement data at each sampling time point with an epoch;

[0017] Step 230, input the inertial navigation measurement data into the inertial navigation extrapolation module for data management and inertial navigation extrapolation to obtain an inertial navigation extrapolation result; the inertial navigation extrapolation result includes an inertial navigation error;

[0018] Step 240, input the GNSS measurement information of each epoch into the GNSS and MIMU integrated navigation module one by one, and determine the observability of the navigation satellite according to the GNSS measurement information;

[0019] In the current epoch, if the navigation satellite is observable, the GNSS and MIMU integrated navigation module fuses the inertial navigation extrapolation result to obtain an integrated navigation positioning result, and re - execute Step 240 for the next epoch; if the navigation satellite is unobservable, execute Step 250;

[0020] Step 250, input the magnetometer measurement data into the magnetometer assistance module, and obtain a reliable attitude result through direction angle calculation and inertial navigation measurement data verification and correction;

[0021] Step 260: When the navigation satellite is not observable, input the GNSS measurement information, the inertial navigation extrapolation result, and the reliable attitude result into the spectrum map matching positioning module based on SIR particle filtering to obtain the spectrum map navigation positioning result, which is used as the integrated navigation positioning result.

[0022] Step 270: Use the spectrum map navigation positioning result to correct the inertial navigation error of the inertial navigation extrapolation result. After clearing the inertial navigation error state, re - execute Step 240 for the next epoch until all epochs are traversed, and then output and save the integrated navigation positioning result.

[0023] In summary, the present invention proposes a navigation method combining satellite, inertial navigation, spectrum map, and magnetometer. Compared with the prior art, the advantages and beneficial effects of the integrated navigation method of the present invention include:

[0024] (1) By using inertial navigation extrapolation, not only can high - precision positioning results be obtained through the combination of GNSS and inertial navigation under observable satellite navigation conditions, but also the speed information of the navigation attitude can be obtained when satellite navigation is not observable.

[0025] (2) Through the auxiliary calculation of the magnetometer and the fusion of inertial navigation measurement data, the azimuth information is provided when satellite navigation is not observable, correcting anomalies and interferences, and improving the navigation positioning accuracy.

[0026] (3) In particular, by combining the speed information of the navigation attitude, the azimuth information, the result information of inertial navigation extrapolation, and the GNSS measurement information when not observable, through spectrum map matching positioning based on SIR particle filtering, the positioning position information when satellite navigation is denied is provided for the platform system, and the cumulative errors of inertial navigation and magnetometer are eliminated, greatly improving the navigation positioning accuracy.

[0027] (4) Through the comprehensive application of satellite, inertial navigation, spectrum map, and magnetometer, the problem of cumulative errors of inertial navigation and magnetometer when satellite navigation is not observable is solved, providing high - precision navigation positioning effects for mobile intelligent platforms such as mobile phones or robots. Brief Description of the Drawings

[0028] Figure 1 It is a flowchart of a navigation method combining satellite, inertial navigation, spectrum map, and magnetometer in the first embodiment of the present invention;

[0029] Figure 2 It is a schematic diagram of the GNSS observable algorithm architecture of a navigation method combining satellite, inertial navigation, spectrum map, and magnetometer applied to a 5G mobile phone in the second embodiment of the present invention;

[0030] Figure 3Schematic diagram of the algorithm architecture when GNSS is unobservable for a navigation method combining satellite, inertial navigation, spectrum map, and magnetometer in the second embodiment of the present invention for a 5G mobile phone. Detailed implementation manners

[0031] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0032] With the development of the mapping and application of outdoor spectrum maps, especially in GNSS-denied (unobservable) environments, spectrum maps can provide important technical supplements for indoor and outdoor seamless navigation and positioning services of mobile intelligent platforms. In view of the problem of micro-inertial navigation and magnetometer error accumulation caused by unobservability of satellite navigation in the navigation and positioning of mobile intelligent platforms in complex environments, the present invention provides a navigation method combining satellite, inertial navigation, spectrum map, and magnetometer, which comprehensively uses various navigation technical means of satellite, inertial navigation, spectrum map, and magnetometer, effectively improves the navigation and positioning accuracy of mobile intelligent platforms equipped with the above multi-sensors, and meets the seamless navigation and positioning requirements in occluded environments.

[0033] In the first embodiment, as shown in Figure 1 the present invention provides a navigation method combining satellite, inertial navigation, spectrum map, and magnetometer, which specifically includes the following steps:

[0034] Step 110, obtaining sensor measurement data of the mobile intelligent platform in real time and storing it in a data file; the sensor measurement data at least includes GNSS measurement information, inertial navigation measurement data, signal strength data, spectrum map, and magnetometer measurement data;

[0035] Step 120, sampling the sensor measurement data from the data file and marking the sensor measurement data at each sampling time point with an epoch;

[0036] Step 130, performing data management and inertial navigation extrapolation on the inertial navigation measurement data to obtain an inertial navigation extrapolation result; the inertial navigation extrapolation result includes inertial navigation errors;

[0037] Step 140, determining the observability of navigation satellites based on the GNSS measurement information of the current epoch; if the navigation satellites are observable, using the inertial navigation extrapolation result and GNSS-inertial navigation integrated navigation to obtain an integrated navigation and positioning result, and re-executing step 140 for the next epoch; if the navigation satellites are unobservable, execute step 150;

[0038] Step 150: Through direction angle calculation and inertial navigation measurement data inspection and correction of the magnetometer measurement data, obtain a reliable attitude result;

[0039] Step 160: After synchronizing the signal strength data and the spectrum map data, combine the inertial navigation extrapolation result and the reliable attitude result, and through spectrum map matching positioning based on SIR particle filtering, obtain a spectrum map navigation positioning result as the integrated navigation positioning result;

[0040] Step 170: Use the spectrum map navigation positioning result to correct the inertial navigation error of the inertial navigation extrapolation result. After clearing the inertial navigation error state, re - execute Step 140 for the next epoch until all epochs are traversed, and then output and save the integrated navigation positioning result.

[0041] Specifically, in Step 110, the mobile intelligent platform loads at least sensors: GNSS, inertial navigation, spectrum map, and magnetometer; the data files at least include: GNSS measurement information file, inertial navigation measurement data file, communication ubiquitous feature measurement file, and magnetometer measurement file;

[0042] The GNSS measurement information file at least includes a measurement file and an ephemeris file; the measurement file receives and records in real - time the observation data for positioning and navigation calculations, and at least includes satellite number, timestamp (time information of the observation data), pseudorange measurement value (error - containing measured distance of satellite signal propagation to the receiver), carrier phase measurement value, Doppler frequency shift, and signal strength; the ephemeris file records the ephemeris data for calculating the position of the satellite at any time, and at least includes satellite number (corresponding to the measurement file), timestamp (time information of the ephemeris data), Keplerian orbital elements (parameters describing the satellite orbit), and satellite clock correction parameter (used to correct the deviation between the satellite clock and the system time); the measurement file and the ephemeris file jointly provide basic data for GNSS positioning to ensure the accuracy and reliability of positioning; one epoch in GNSS measurement refers to the sampling time point for collecting GNSS measurement information at time intervals , where , is the total number of epochs of GNSS measurement information, ;

[0043] The inertial navigation measurement data file receives and records in real time the inertial navigation measurement data collected by the mobile intelligent platform during movement, and is used for the inertial navigation system to estimate navigation state parameters including position, velocity, and attitude; the inertial navigation measurement data file includes at least header information and inertial navigation measurement data, the header information includes at least a timestamp, a sampling rate, sensor information, and calibration parameters, and the inertial navigation measurement data includes at least a timestamp, a sampling sequence number, accelerometer data, and gyroscope data; the accelerometer data includes accelerometer velocity data, and the gyroscope data includes gyroscope angle data; similarly, one epoch in inertial measurement , refers to the sampling time point for obtaining inertial measurement data at time intervals , where , is the total number of epochs of inertial measurement data, , and ;

[0044] The communication ubiquitous feature measurement file includes at least a signal strength data file for receiving and storing signal strength data in real time, and a spectrum map file that has been constructed and can be updated in real time; the signal strength data file includes at least a timestamp, base station information, frequency band information, signal strength, and signal quality; the spectrum map file includes at least map location information, signal strength data corresponding to the location, environmental feature parameters, frequency information, and timestamp information of the collected data; one epoch of output signal strength data , refers to the sampling time point for collecting signal strength data at time intervals , where , is the total number of epochs of inertial measurement data, ;

[0045] The magnetometer measurement file records the magnetometer measurement data collected by the mobile intelligent platform during dynamic operation, and is used for attitude estimation and direction measurement; the magnetometer measurement data includes at least a timestamp, a sampling sequence number, and magnetic field strength data.

[0046] Specifically, in step 130, data management and inertial navigation extrapolation are performed on the inertial navigation measurement data to obtain an inertial navigation extrapolation result, including:

[0047] Read the inertial navigation measurement information of each epoch one by one , and temporarily store the inertial navigation measurement information of each epoch in the inertial navigation measurement data buffer structure;

[0048] Let be the current epoch of GNSS measurement information, and from to before (excluding and ), a total of one epoch accumulate the gyro angle increment and accelerometer speed increment in the inertial navigation measurement information of to obtain the change amount of the navigation state parameters; among them,

[0049] ;

[0050] Take the change amount of the navigation state parameters as input data, and use inertial navigation extrapolation to calculate and predict the inertial navigation measurement data at as the inertial navigation extrapolation result and store it in the inertial navigation extrapolation data file.

[0051] Furthermore, in step 140, use the inertial navigation extrapolation result and GNSS / inertial integrated navigation to obtain the integrated navigation positioning result, including:

[0052] Use the inertial navigation extrapolation result to synchronize the inertial navigation measurement data and GNSS measurement information at ;

[0053] Use the GNSS measurement information and inertial navigation measurement data at the initial to determine the initial navigation state parameters of the platform and realize the initial alignment of GNSS and inertial navigation;

[0054] Through tight-coupled EKF (Extended Kalman Filter) measurement update, predict the navigation state parameters to obtain the integrated navigation positioning result; in this process, the GNSS measurement information and unsynchronized inertial navigation measurement data are fused through a tight-coupled strategy, suppressing the errors of a single sensor, and using the GNSS measurement information to correct the prediction error of the navigation state parameters, estimating and suppressing the inertial navigation error.

[0055] The said step 150 includes:

[0056] Read the magnetometer measurement data from the magnetometer measurement file;

[0057] Calculate the azimuth angle of the mobile intelligent platform according to the magnetometer measurement data ;

[0058] Use the inertial navigation measurement data to test and correct the azimuth angle, improving the navigation positioning accuracy due to correcting anomalies and interference;

[0059] Output a reliable attitude result that fuses the magnetometer measurement data and the inertial navigation measurement data.

[0060] Furthermore, the said step 160 includes:

[0061] Obtain the signal strength data and the spectrum map from the communication ubiquitous feature measurement file;

[0062] Read the current epoch Signal strength data, and update the spectrum map in real time;

[0063] Judge the changes before and after the real-time update of the spectrum map; if there are changes, synchronize the signal strength data of the current epoch with the spectrum map; if there are no changes, replace the spectrum map with the offline spectrum map;

[0064] Through the time update and measurement update of the SIR (Sampling Importance Resampling) particle filter, perform spectrum map matching positioning to obtain the spectrum map navigation positioning result as the integrated navigation positioning result, including:

[0065] Use inertial navigation measurement data to obtain the initial inertial position ;

[0066] Based on the initial inertial position , initialize the particle swarm;

[0067] Propagate the particle swarm based on the inertial motion equation: , where is the time identifier, is the position vector of the inertial navigation, is the particle identifier, is the position increment; represents the position increment of the inertial navigation at time relative to time represents the position vector of the inertial navigation at time

[0068] Calculate the particle state value , where is the observation vector of the signal strength corresponding to the particle in the spectrum map, is the two-dimensional coordinate matrix of the particle swarm.

[0069] Calculate the particle observation value , and update the weighted particle value , calculate the number of effective particles ;

[0070] When the number of effective particles is less than the preset threshold , perform importance resampling (SIR);

[0071] When , estimate the position and velocity state values of the mobile intelligent platform: ;

[0072] Based on perform particle resampling in the next epoch navigation positioning.

[0073] Navigation and positioning result using spectrum map Correct the inertial navigation error of the inertial navigation extrapolation result. After clearing the inertial navigation error state, re - perform particle resampling for the next epoch.

[0074] Another embodiment of the present invention provides a navigation device combining satellite, inertial navigation, spectrum map, and magnetometer. The steps of the navigation method combining satellite, inertial navigation, spectrum map, and magnetometer in the foregoing embodiment are implemented using the device. The device includes the following modules:

[0075] The first module is used to obtain sensor measurement data of the mobile intelligent platform in real - time and store it in a data file; the sensor measurement data includes at least GNSS measurement information, inertial navigation measurement data, signal strength data, spectrum map, and magnetometer measurement data;

[0076] The second module is used to sample the sensor measurement data from the data file and mark the sensor measurement data at each sampling time point with an epoch;

[0077] The third module is used to perform data management and inertial navigation extrapolation on the inertial navigation measurement data to obtain an inertial navigation extrapolation result; the inertial navigation extrapolation result includes an inertial navigation error;

[0078] The fourth module is used to determine the observability of navigation satellites based on the GNSS measurement information of the current epoch; if the navigation satellites are observable, use the inertial navigation extrapolation result and GNSS - inertial navigation integrated navigation to obtain an integrated navigation and positioning result, and return to the fourth module for the next epoch; if the navigation satellites are unobservable, connect to the fifth module;

[0079] The fifth module is used to obtain a reliable attitude result by resolving the direction angle of the magnetometer measurement data and verifying and correcting it with the inertial navigation measurement data;

[0080] The sixth module is used to synchronize the signal strength data and the spectrum map, and then combine the inertial navigation extrapolation result and the reliable attitude result to obtain a spectrum map navigation and positioning result through spectrum map matching positioning based on SIR particle filtering as the integrated navigation and positioning result;

[0081] The seventh module is used to correct the inertial navigation error of the inertial navigation extrapolation result using the spectrum map navigation and positioning result. After clearing the inertial navigation error state, return to the fourth module for the next epoch until all epochs are traversed, and output and save the integrated navigation and positioning result.

[0082] In the real - world social life scenario, with the full coverage of outdoor 5G static base - station systems, mobile intelligent devices can conveniently obtain a stable 5G spectrum map to provide positioning services. Currently or in the future, most mobile intelligent devices can be equipped with sensors such as satellites, 5G spectrum maps, inertial navigation, and magnetometers. Therefore, implementing a combined navigation and positioning system for mobile intelligent devices based on satellites, 5G spectrum maps, inertial navigation, and magnetometers has broad application value.

[0083] In the third embodiment of the present invention, the navigation method combining the satellite, inertial navigation, spectrum map, and magnetometer is applied to a 5G mobile phone, which is a mobile intelligent platform, to meet the high - precision navigation and positioning requirements in complex environments suitable for outdoor - indoor environment switching. It should be noted that the inertial navigation method adopted in this embodiment is a micro - inertial navigation mode based on MIMU. For the sake of simplicity in description, MIMU and the micro - inertial navigation based on MIMU will not be distinguished in the following narrative. As Figure 2 shown, the present invention protects the application of the aforementioned navigation method combining the satellite, inertial navigation, spectrum map, and magnetometer on a 5G mobile phone. The method includes:

[0084] Step 210: Real - time obtain the sensor measurement data loaded on the 5G mobile phone and store it in a data file; the sensor measurement data at least includes GNSS measurement information, inertial navigation measurement data, signal strength data, spectrum map, and magnetometer measurement data; a GNSS and MIMU combined navigation module, an inertial navigation extrapolation module, a spectrum map matching and positioning module based on SIR particle filtering, a magnetometer assistance module, and a system error estimation module are installed on the 5G mobile phone.

[0085] Step 220: Sample the sensor measurement data from the data file and mark the sensor measurement data at each sampling time point with an epoch.

[0086] Step 230: Input the inertial navigation measurement data into the inertial navigation extrapolation module for data management and inertial navigation extrapolation to obtain an inertial navigation extrapolation result; the inertial navigation extrapolation result includes an inertial navigation error.

[0087] Step 240: Input the GNSS measurement information of each epoch into the GNSS and MIMU combined navigation module one by one, and determine the observability of navigation satellites based on the GNSS measurement information.

[0088] In the current epoch, if the navigation satellite is observable, as Figure 2 shown, the GNSS and MIMU combined navigation module fuses the inertial navigation extrapolation result to obtain a combined navigation and positioning result, and re - executes Step 240 for the next epoch; if the navigation satellite is unobservable, then execute Step 250.

[0089] Step 250: Input the magnetometer measurement data into the magnetometer assistance module, as Figure 3As shown, reliable attitude results are obtained through direction angle calculation and inspection and correction of inertial navigation measurement data;

[0090] Step 260, when the navigation satellite is not observable, as Figure 3 shown, input the GNSS measurement information, the inertial navigation extrapolation result, and the reliable attitude result into the spectrum map matching positioning module based on SIR particle filtering to obtain the spectrum map navigation positioning result as the integrated navigation positioning result;

[0091] Step 270, use the spectrum map navigation positioning result to correct the inertial navigation error of the inertial navigation extrapolation result. After clearing the inertial navigation error state, re - execute Step 240 for the next epoch until all epochs are traversed, and output and save the integrated navigation positioning result.

[0092] Furthermore, the 5G mobile phone is at least loaded with sensors: GNSS, MIMU, 5G spectrum map, and magnetometer; the data files include: GNSS measurement information file, inertial navigation measurement data file, communication ubiquitous feature measurement file, and magnetometer measurement file.

[0093] The GNSS measurement information file at least includes the inertial navigation measurement data of the measurement file (Obs.dat) and the ephemeris file (Eph.dat); the inertial navigation measurement data file contains inertial navigation measurement data, named MIMU data.dat; the communication ubiquitous feature measurement file at least includes the signal strength data file (RSS.dat) and the spectrum map file (mapData_0.mat), which are used to store signal strength data and spectrum maps respectively; the magnetometer measurement file records the 5G mobile phone magnetometer measurement data for attitude estimation and direction measurement.

[0094] The process of Step 260, as Figure 3 shown, includes:

[0095] Obtain signal strength data and the 5G spectrum map from the communication ubiquitous feature measurement file;

[0096] Read the signal strength data of the current epoch and update the spectrum map in real - time;

[0097] Judge the changes before and after the real - time update of the spectrum map; if there are changes, synchronize the signal strength data of the current epoch with the 5G spectrum map; if there are no changes, replace the 5G spectrum map with the offline spectrum map;

[0098] Through the time update and measurement update of SIR particle filtering, perform spectrum map matching positioning to obtain the spectrum map navigation positioning result as the integrated navigation positioning result, including:

[0099] Use inertial navigation measurement data to obtain the initial inertial navigation position ;

[0100] Initialize the particle swarm based on the initial position of the inertial navigation; Initialize the particle swarm;

[0101] Propagate the particle swarm based on the inertial navigation equation of motion: , where is the time stamp, is the position vector of the inertial navigation, is the particle identifier, is the position increment; denotes the position increment of the inertial navigation at time relative to time denotes the position vector of the inertial navigation at time

[0102] Calculate the particle state value , where is the observation vector of the signal strength corresponding to the particle in the spectrum map, is the two-dimensional coordinate matrix of the particle swarm;

[0103] Calculate the particle observation value , and update the weighted particle value , calculate the number of effective particles ;

[0104] When the number of effective particles is less than the preset threshold , perform importance resampling (SIR);

[0105] When , estimate the positioning position and speed state value of the 5G mobile phone: ;

[0106] Based on Perform particle resampling in the next epoch navigation and positioning.

[0107] Furthermore, store the inertial navigation extrapolation result in step 230 in the file INS_MAP_Position.dat; store the integrated navigation and positioning result obtained by using the GNSS and MIMU integrated navigation module in step 240 in the file GNSS_MIMU.dat; store the integrated navigation and positioning result obtained in step 270 in the file All_NavResult.mat.

[0108] Aiming at the technical problem of providing high-precision and high environmental adaptability integrated navigation and positioning for mobile intelligent platforms, through the methods and devices proposed in the above embodiments, the present invention uses GNSS and inertial navigation integrated navigation to provide high-precision positioning results in an environment where satellite navigation is not denied (satellite navigation is observable); uses inertial navigation extrapolation to provide speed information when satellite navigation is denied (satellite navigation is not observable); uses magnetometer calculation assistance to provide azimuth information when satellite navigation is denied; in particular, through spectrum map matching positioning based on SIR particle filtering, provides positioning position information for the platform system when satellite navigation is denied, and eliminates the error accumulation of inertial navigation and magnetometer, greatly improving the navigation and positioning accuracy. Through the comprehensive application of satellites, inertial navigation, spectrum maps and magnetometers, the present invention solves the problem of error accumulation of inertial navigation and magnetometer when satellite navigation is unobservable, and provides a new solution idea for obtaining high-precision navigation and positioning effects for mobile intelligent platforms such as mobile phones or robots.

[0109] On the other hand, in another embodiment of the present invention, a computer device is provided. The device may be a server. The device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the device is used to provide computing and control capabilities. The memory of the device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the device is used to store integrated navigation and positioning data. The network interface of the device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements the navigation method of the combination of the satellite, inertial navigation, spectrum map and magnetometer.

[0110] Those skilled in the art can understand that the description of the technical features of the device in the above embodiments does not constitute a limitation on all devices to which the present invention is applied. Specific devices may include more or fewer components, or combine certain components, or have different component arrangements.

[0111] In another embodiment, a storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the aforementioned navigation method of the combination of the satellite, inertial navigation, spectrum map and magnetometer.

[0112] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0113] Matters not described in the present invention are well-known techniques.

[0114] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0115] The above-described embodiments only represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.

Claims

1. A navigation method combining satellite, inertial navigation, spectral map, and magnetometer, characterized in that, Including: Step 110: Obtain the sensor measurement data of the mobile intelligent platform in real time and store it in a data file; The sensor measurement data at least includes GNSS measurement information, inertial navigation measurement data, signal strength data, spectrum map, and magnetometer measurement data; Step 120: Sample the sensor measurement data from the data file and mark the sensor measurement data at each sampling time point with an epoch; Step 130: Perform data management and inertial navigation extrapolation on the inertial navigation measurement data to obtain an inertial navigation extrapolation result; the inertial navigation extrapolation result includes inertial navigation errors; Step 140: Determine the observability of navigation satellites based on the GNSS measurement information of the current epoch; If the navigation satellite is observable, use the inertial navigation extrapolation result and the GNSS-inertial integrated navigation to obtain an integrated navigation positioning result, and re-execute Step 140 for the next epoch; if the navigation satellite is unobservable, execute Step 150; Step 150: Through direction angle calculation and inertial navigation measurement data verification and correction of the magnetometer measurement data, obtain a reliable attitude result; Step 160: After synchronizing the signal strength data and the spectrum map, combine the inertial navigation extrapolation result and the reliable attitude result, and obtain a spectrum map navigation positioning result through spectrum map matching positioning based on SIR particle filtering as the integrated navigation positioning result; Step 170: Use the spectrum map navigation positioning result to correct the inertial navigation error of the inertial navigation extrapolation result. After clearing the inertial navigation error state, re-execute Step 140 for the next epoch until all epochs are traversed, and output and save the integrated navigation positioning result.

2. The navigation method of the satellite, inertial navigation, spectral map, and magnetometer combination according to claim 1, wherein In Step 110, the data file at least includes: a GNSS measurement information file, an inertial navigation measurement data file, a communication ubiquitous feature measurement file, and a magnetometer measurement file; The GNSS measurement information file is used to store GNSS measurement information, at least including a measurement file for storing observation data and an ephemeris file for storing ephemeris data; The inertial navigation measurement data file is used to store inertial navigation measurement data; the inertial navigation measurement data at least includes accelerometer data and gyroscope data; the accelerometer data includes accelerometer velocity data, and the gyroscope data includes gyroscope angle data; The communication ubiquitous feature measurement file at least includes a signal strength data file for real-time receiving and storing signal strength data, and a spectrum map file that has been completed and can be updated in real time; the spectrum map file provides a spectrum map, at least including map position information, signal strength data corresponding to the position, environmental feature parameters, frequency information, and time stamp information of the collected data; The magnetometer measurement file contains magnetometer measurement data and is used for attitude estimation and direction measurement.

3. The navigation method of the satellite, inertial navigation, spectral map, and magnetometer combination according to claim 2, characterized in that In Step 120, sampling the sensor measurement data from the data file and marking the sensor measurement data at each sampling time point with an epoch includes: Sampling GNSS measurement information from the GNSS measurement information file, one epoch of GNSS measurement information , refers to the time interval The sampling time point for collecting GNSS measurement information, where , is the total number of epochs of GNSS measurement information, ; Sampling inertial navigation measurement data from an inertial navigation measurement data file, one epoch of the inertial navigation measurement data , refers to the sampling time point for obtaining inertial measurement data at time intervals , where , is the total number of epochs of inertial measurement data, , and ; Collect signal strength data from the signal strength data file, where an epoch of the signal strength data refers to the sampling time point for collecting the signal strength data at a time interval , and among them, , is the total number of epochs of the signal strength data, .

4. The navigation method of the satellite, inertial navigation, spectrum map, and magnetometer combination according to claim 3, characterized in that In Step 130, performing data management and inertial navigation extrapolation on the inertial navigation measurement data to obtain an inertial navigation extrapolation result includes: Read the inertial navigation measurement information of each epoch one by one and temporarily store the inertial navigation measurement information of a single epoch into the inertial navigation measurement data buffer structure; Let be the current epoch of GNSS measurement information. Cumulatively sum the gyro angle increments and accelerometer velocity increments in the inertial navigation measurement information for a total of epochs from after to before to obtain the change in the navigation state parameters, where: ​ ； Taking the change amount of the navigation state parameter as input data, inertial navigation extrapolation is used to calculate and predict the inertial navigation measurement data at as the inertial navigation extrapolation result.

5. The navigation method of the satellite, inertial navigation, spectral map, and magnetometer combination according to claim 4, wherein In Step 140, using the inertial navigation extrapolation result and the GNSS-inertial integrated navigation to obtain an integrated navigation positioning result includes: Synchronize the inertial navigation measurement data and GNSS measurement information at using the inertial navigation extrapolation result ​ Using the GNSS measurement information and inertial navigation measurement data at the initial time, determine the initial navigation state parameters of the platform, and realize the integrated initial alignment of GNSS and inertial navigation; Predict the navigation state parameters through tightly coupled extended Kalman filter measurement update to obtain the integrated navigation positioning result.

6. The navigation method of the satellite, inertial navigation, spectrum map, and magnetometer combination according to claim 5, characterized in that, The step 150 includes: Read the magnetometer measurement data from the magnetometer measurement file; Calculating the azimuth angle of a mobile intelligent platform based on magnetometer measurement data ; Use the inertial navigation measurement data to test and correct the azimuth angle; Output a reliable attitude result that fuses the magnetometer measurement data and the inertial navigation measurement data.

7. The navigation method of the satellite, inertial navigation, spectrum map, and magnetometer combination according to claim 6, characterized in that, The step 160 includes: Obtain the signal strength data and the spectrum map from the communication ubiquitous feature measurement file; Read the current epoch signal strength data and update the spectrum map in real time; Judge the changes in the spectrum map before and after real-time update; if there are changes, synchronize the signal strength data and the spectrum map of the current epoch; if there are no changes, replace the spectrum map with the offline spectrum map; Perform spectrum map matching positioning through the time update and measurement update of the SIR particle filter to obtain the spectrum map navigation positioning result as the integrated navigation positioning result.

8. The navigation method of the satellite, inertial navigation, spectrum map, and magnetometer combination according to claim 7, characterized in that, Performing spectrum map matching positioning through the time update and measurement update of the SIR particle filter to obtain the spectrum map navigation positioning result includes: Obtaining the initial position of inertial navigation using inertial navigation measurement data ; Initializing the particle swarm based on the initial position of inertial navigation . Propagate the particle swarm based on the inertial navigation motion equation: , where is the time identifier, is the position vector of inertial navigation, is the particle identifier, is the position increment; denotes the position increment of inertial navigation at time relative to time denotes the position vector of inertial navigation at time Calculate the particle state value , where is the observation vector of the signal intensity data corresponding to the particle in the spectrum map, is the two-dimensional coordinate matrix of the particle swarm; Calculate the particle observation value , and update the weighted particle value , calculate the number of effective particles ; When the number of effective particles is less than the preset threshold , importance resampling is performed; When , estimate the position and velocity state values of the mobile intelligent platform: ; Based on perform particle resampling in the next epoch navigation and positioning.

9. Application of the navigation method of the satellite, inertial navigation, spectrum map, and magnetometer combination according to any one of claims 1 to 8 on a 5G mobile phone to achieve combined navigation and positioning of the 5G mobile phone, wherein the inertial navigation adopts a micro-inertial navigation mode based on MIMU, characterized in that, The method includes: Step 210, obtain the sensor measurement data loaded on the 5G mobile phone in real time and store it in the data file; the sensor measurement data at least includes GNSS measurement information, inertial navigation measurement data, signal strength data, spectrum map, and magnetometer measurement data; a GNSS and MIMU integrated navigation module, an inertial navigation extrapolation module, a spectrum map matching positioning module based on the SIR particle filter, a magnetometer assistance module, and a system error estimation module are carried on the 5G mobile phone; Step 220, sample the sensor measurement data from the data file and mark the sensor measurement data at each sampling time point with an epoch; Step 230, input the inertial navigation measurement data into the inertial navigation extrapolation module for data management and inertial navigation extrapolation to obtain the inertial navigation extrapolation result; the inertial navigation extrapolation result includes inertial navigation errors; Step 240, input the GNSS measurement information of each epoch into the GNSS and MIMU integrated navigation module one by one, and determine the observability of the navigation satellites according to the GNSS measurement information; In the current epoch, if the navigation satellites are observable, the GNSS and MIMU integrated navigation module fuses the inertial navigation extrapolation result to obtain the integrated navigation positioning result, and re-execute step 240 for the next epoch; if the navigation satellites are unobservable, execute step 250; Step 250, input the magnetometer measurement data into the magnetometer assistance module, and obtain a reliable attitude result through direction angle calculation and inertial navigation measurement data test and correction; Step 260, when the navigation satellites are unobservable, input the GNSS measurement information, the inertial navigation extrapolation result, and the reliable attitude result into the spectrum map matching positioning module based on the SIR particle filter to obtain the spectrum map navigation positioning result as the integrated navigation positioning result; Step 270, use the spectrum map navigation positioning result to correct the inertial navigation error of the inertial navigation extrapolation result. After clearing the inertial navigation error state, re-execute step 240 for the next epoch until all epochs are traversed, and output and save the integrated navigation positioning result.

Images