A GNSS / INS vector depth combined arrow-borne navigation and positioning device

Abstract

The present invention discloses a GNSS / INS vector deep combination arrow-borne navigation and positioning device, belonging to the field of combined navigation technology. It includes a high temperature resistant receiving antenna, a receiving radio frequency module, an inertial measurement module, and a baseband processing module; it receives space satellite navigation signals through a high temperature resistant receiving antenna, converts them into digital intermediate frequency signals through the receiving radio frequency module, and measures the arrow body inertial navigation data through the inertial measurement module, realizes the combined processing and high dynamic capture of navigation signals in the baseband processing module, adopts the "open loop + correction" framework to perform vector tracking of navigation signals, completes the navigation message frame, and performs message analysis after bit synchronization, and finally completes the positioning solution to realize the output of arrow body speed and position information. The present invention has the ability of precise positioning under high speed and complex posture, and has the ability of anti-interference under high noise and multipath environment, and can realize effective navigation and positioning with high continuity and high precision in a high dynamic arrow-borne environment.

Description

Technical Field

[0001] The invention belongs to the technical field of combined navigation, and in particular relates to an arrow-borne navigation and positioning device of a GNSS / INS vector depth combination. Background Art

[0002] In modern aerospace technology, the navigation and positioning of rocket separators and other highly dynamic aircraft face severe challenges. After completing the mission, the separator separates from the main body and enters a free fall or high-speed flight state, accompanied by high-speed and complex attitude rotation and acceleration changes. Traditional GNSS navigation technology is difficult to ensure stable tracking of navigation signals in such a high-dynamic environment, and due to the influence of Doppler frequency shift, the traditional receiver capture process is too long, affecting the timeliness and accuracy of positioning. In addition, although the inertial navigation system (INS) has the ability to autonomously position for a short time, its measurement errors will accumulate over time and cause drift, and it is difficult to meet the high-precision positioning requirements by relying solely on INS.

[0003] High-dynamic aircraft are affected by their attitude and structure during flight, and may also experience signal weakening and shielding conditions. Especially in high-speed rotation, satellite signals are easily interrupted, and traditional receivers take a long time to recapture after being locked. At the same time, the quality of navigation signals is significantly reduced due to electromagnetic interference and multipath problems caused by the onboard. These factors make it difficult to cope with complex aerospace navigation requirements using traditional GNSS or INS alone. Therefore, studying more robust navigation methods that can quickly recapture and maintain stable tracking under extreme conditions has become an important challenge for current technology. Summary of the invention

[0004] In view of the above problems, the present invention proposes a GNSS / INS vector deep combination rocket-borne navigation and positioning device. The device integrates high-dynamic signal capture, fast recapture after loss of lock, multipath interference processing and other functions through the vector deep combination technology of GNSS and INS, which greatly improves its positioning capability in high-dynamic aircraft and can achieve high-reliability and high-continuity positioning in rocket-borne high-dynamic environments.

[0005] The technical solution adopted by the present invention is:

[0006] A GNSS / INS vector depth combined arrow-borne navigation and positioning device, comprising a high temperature resistant receiving antenna, a receiving radio frequency module, an inertial measurement module, and a baseband processing module;

[0007] The high temperature resistant receiving antenna is an active antenna, which is used to convert the space satellite navigation signal into an electrical signal, and output it after pre-selection filtering, low noise amplification, and bandpass filtering;

[0008] The receiving RF module includes a low noise amplifier unit, a RF filter unit and an RNSS RF unit, wherein the low noise amplifier unit is used to perform low noise amplification on the signal output by the high temperature resistant receiving antenna, the RF filter unit adopts bandpass filtering, and the RNSS RF unit is used to perform mixing, intermediate frequency filtering, automatic gain control and analog-to-digital conversion on the satellite navigation signal, and finally output a 4-bit digital intermediate frequency signal to the baseband processing module;

[0009] The inertial measurement module includes a high-precision three-axis accelerometer and a three-axis gyroscope, which are used to measure inertial navigation information including speed and acceleration, and output the inertial navigation information to the baseband processing module;

[0010] The baseband processing module is used to realize navigation signal processing and information resolution.

[0011] Furthermore, the high temperature resistant receiving antennas are two active antennas, and the receiving RF module includes two groups of low noise amplifier units, RF filter units and RNSS RF units, which process the output signal of one high temperature resistant receiving antenna respectively.

[0012] Furthermore, the baseband processing module includes:

[0013] The inertial navigation information preprocessing submodule preprocesses the velocity and acceleration information generated by the inertial measurement module, corrects the scale factor error and installation error of the accelerometer and gyroscope in the IMU, completes self-calibration during the system startup phase to remove the zero bias value, and converts the linear acceleration and angular velocity data generated by the accelerometer and gyroscope in the body coordinate system to the ground-fixed coordinate system;

[0014] The signal combining submodule combines the two digital intermediate frequency signals transmitted by the receiving RF module, adopts the signal-to-noise ratio weighted selective combining algorithm, performs real-time signal-to-noise ratio measurement on the input signal, and combines the two navigation signals in a weighted manner based on the measured value;

[0015] The high dynamic capture submodule uses frequency block search and fast Fourier transform to traverse the high dynamic Doppler range, uses a parallel correlator group and a multi-point parallel fast Fourier transform pipeline mode to quickly search for navigation signals within the frequency block, performs a threshold check on the detected signal, and sends the successfully captured signal frequency and pseudo code phase information to the vector tracking submodule;

[0016] The vector tracking submodule receives the signal capture parameters of the high dynamic capture submodule and the attitude and velocity information of the inertial navigation information preprocessing submodule; drives the code tracking loop through the carrier frequency, drives the carrier tracking loop update through the carrier acceleration, and dynamically adjusts the carrier loop bandwidth according to the real-time signal-to-noise ratio and Doppler frequency shift information; uses the geographic system as the navigation coordinate system, uses the position, velocity, and acceleration as the navigation state, and uses the Kalman filter algorithm for navigation update; isolates the weak signal channel based on the signal-to-noise ratio estimate, restores the carrier frequency of the lost signal through the navigation state update, and re-establishes tracking; automatically switches the extended Kalman filter and the unscented Kalman filter to fuse the IMU data and GNSS measurement data according to the navigation state;

[0017] The navigation synchronization submodule uses the histogram method and NH coding method to complete bit synchronization, and realizes frame synchronization through continuous data matching and BCH decoding. After synchronization is completed, the navigation message information is parsed;

[0018] The navigation solver module extracts the observation information of pseudocode phase and carrier phase from the signal channel, calculates the pseudorange and Doppler frequency shift from the satellite to the receiver; performs delay correction on the pseudorange and time data to compensate for the delay caused by the ionosphere and troposphere during signal propagation; and uses the least squares method to complete the three-dimensional position, velocity and time offset calculation based on the pseudorange and satellite ephemeris data, time information and correction parameters analyzed by the navigation synchronization submodule.

[0019] Furthermore, in the high dynamic capture submodule, the correlator group correlates the received input sampled data and the locally generated signal, obtains the amplitude of the I / Q correlation result, and then performs 128-point pipeline FFT processing; fills zero values ​​before FFT processing to reduce processing losses; compares the FFT processing result with the threshold value, and stores the qualified amplitude value and the corresponding time domain and frequency domain values ​​into the register.

[0020] Furthermore, the vector tracking submodule converts the carrier frequency into the code frequency to drive the code tracking loop, and drives the carrier tracking loop to update through the carrier acceleration. The calculation formula of the code NCO driving frequency is:

[0021]

[0022] In the formula, is the code NCO driving frequency, is the carrier NCO driving frequency, F rf is the nominal frequency of the RF carrier, F co is the code nominal frequency;

[0023] Carrier NCO driving frequency It reflects the state of the current channel open-loop tracking, and calculates the pseudorange ρ′ and pseudorange rate based on the position and velocity. As the expected value of channel tracking, the code phase correction Δτ and carrier drive frequency correction are obtained by difference

[0024]

[0025] In the formula, λ co is the code length, λ ca is the carrier wavelength, t v is the receiver clock frequency error.

[0026] Furthermore, the vector tracking submodule uses the Kalman filter algorithm to perform navigation updates as follows:

[0027]

[0028] Where L is latitude, λ is longitude, h is height, and v is n =[v n ,v e ,v d ] is the speed in the geographic system, a n =[a n ,a e ,a d ] is the acceleration in the geographic system, t r is the receiver clock error, t v is the receiver clock frequency difference, R M , R N are the curvature radii of the local meridian and the meridian respectively, T is the navigation update period, the symbol “^” is the status mark after the navigation update, and the symbol “-” is the status mark before the navigation update;

[0029] Navigation filtering uses the Kalman filter algorithm, switching between extended Kalman filter and unscented Kalman filter according to the navigation state. The state variable is 11 dimensions, as shown below:

[0030] X=[[δp n ,δv n ,δa n ,δt r ,δt v ]] T

[0031] In the formula, δp n =[δp n ,δp e ,δp d ] is the position error in the geographic system, δv n =[δv n ,δv e ,δv d ] is the velocity error in the geographic system, δa n=[δa n ,δa e ,δa d ] is the acceleration error in the geographic system, δt r is the receiver clock error, δt v is the receiver clock frequency error.

[0032] The beneficial effects of the present invention compared with the prior art are:

[0033] (1) The present invention is suitable for arrow-borne high-dynamic navigation environments and can achieve high-continuity and high-precision navigation positioning output.

[0034] (2) The present invention adopts an INS-assisted vector tracking algorithm to enhance the weak signal tracking stability and accelerate the lock-recapture process.

[0035] (3) The present invention adopts dual-antenna navigation signal combining technology to improve the signal continuous receiving capability under dynamic rotation conditions.

[0036] (4) The present invention adopts multipath interference processing and signal quality control strategies, has the ability to resist signal interference in complex electromagnetic environments, and has the ability to accurately locate under high noise and multipath interference.

[0037] (5) The present invention adopts a high-dynamic signal rapid capture technology that combines matched filtering (PMF) with fast Fourier transform (FFT).

[0038] (6) In an environment with fluctuating signal quality or weak signal, the present invention can effectively recover weak signals through INS-assisted vector tracking algorithm and adaptive bandwidth adjustment technology, thereby ensuring the stability and accuracy of positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the structure of the device according to the embodiment of the present invention.

[0040] Figure 2 It is a schematic diagram of the high dynamic capture principle of the device according to an embodiment of the present invention.

[0041] Figure 3 Schematic diagram of the vector tracking principle of the device according to the embodiment of the present invention. DETAILED DESCRIPTION

[0042] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0043] A GNSS / INS vector deep combination rocket navigation and positioning device, which can be implemented based on FPGA+DSP architecture, is suitable for rocket-borne high-dynamic environment, and realizes high-precision and high-dynamic rocket-borne navigation through GNSS / INS vector deep combination algorithm. The device mainly includes a high-temperature resistant receiving antenna, a receiving RF module, an inertial measurement module and a baseband processing module, such as Figure 1 As shown. The functions of each module are as follows:

[0044] The high temperature resistant receiving antenna uses two active high temperature resistant receiving antennas. The antenna material is high temperature resistant ceramics. It receives broadband signals of the BDS / GPS dual system and has high temperature tolerance. The receiving antenna converts the space satellite navigation signal into an electrical signal, which is output after pre-selection filtering, low noise amplification and bandpass filtering.

[0045] The receiving RF module converts the navigation signal output by the high temperature resistant receiving antenna into a digital intermediate frequency signal suitable for baseband processing. The navigation signal output by the high temperature resistant receiving antenna is further amplified by the low noise amplifier unit, and then bandpass filtered to eliminate high frequency interference and image signals, complete signal down conversion and intermediate frequency filtering, as well as automatic gain control (AGC) and analog-to-digital conversion (ADC), and finally output a 4-bit digital intermediate frequency signal.

[0046] The inertial measurement module contains a three-axis accelerometer and a three-axis gyroscope to provide high-precision inertial data. The inertial measurement module can self-calibrate and measure acceleration and angular velocity information to provide detailed inertial navigation information for the device. Inertial data is output at a specified frequency through a fixed protocol.

[0047] The baseband processing module realizes navigation signal processing and navigation positioning solution, which includes a signal combining sub-module, a high dynamic capture sub-module, an inertial navigation information pre-processing sub-module, a vector tracking sub-module, a navigation synchronization sub-module and a navigation solution sub-module.

[0048] Among them, the signal combining submodule adopts the signal-to-noise ratio weighted selective combining algorithm to complete the input signal combining, effectively handling rapid posture changes and multipath interference.

[0049] The high dynamic capture submodule uses "frequency block search" combined with fast Fourier transform (FFT) to traverse the high dynamic Doppler range to achieve rapid signal capture, such as Figure 2As shown. The capture input is the downsampled digital intermediate frequency data, and the code matched filter group contains 420 groups of correlators. The input sampled data received in the correlator group is correlated with the locally generated signal, and the amplitude of the I / Q correlation result is calculated and then a 128-point pipeline FFT process is performed. Zero values ​​are filled before FFT processing to reduce processing loss. The FFT processing result is compared with the threshold value, and the amplitude value that meets the conditions and the corresponding time domain and frequency domain values ​​are stored in the register for subsequent processing.

[0050] The inertial navigation information preprocessing submodule mainly processes the inertial data generated by the inertial measurement module and performs error compensation, zero bias removal and coordinate conversion.

[0051] The vector tracking principle of the vector tracking submodule is as follows Figure 3 The tracking module converts the code frequency into carrier frequency to drive the code tracking loop, and drives the carrier tracking loop update through carrier acceleration. The calculation formula of the code NCO driving frequency is:

[0052]

[0053] In the formula, is the code NCO driving frequency, is the carrier NCO driving frequency, F rf is the nominal frequency of the RF carrier, F co is the code nominal frequency. Carrier NCO driving frequency Reflects the current channel open-loop tracking state, pseudorange ρ′ and pseudorange rate calculated based on position and velocity is the expected value of channel tracking, and the difference between the two can be used to obtain the code phase correction Δτ and the carrier drive frequency correction

[0054]

[0055] In the formula, λ co is the code length, λ ca is the carrier wavelength, t v is the receiver clock frequency difference, dimensionless. Extracting the code phase offset and carrier frequency deviation can obtain the channel pseudorange, pseudorange rate measurement value ρ and With the expected value ρ′ and The pseudorange and pseudorange rate residual values ​​δρ and

[0056] The vector tracking framework of the vector tracking submodule uses position, velocity, and acceleration as navigation states, and selects the geographic system as the navigation coordinate system. Navigation updates are based on the constant acceleration criterion, assuming that the acceleration remains unchanged within the update interval. At the same time, the receiver clock error is updated, assuming that the clock frequency difference remains unchanged within the update interval. The navigation update process is as follows:

[0057]

[0058] Where L is latitude, λ is longitude, h is height, and v is n =[v n ,v e ,v d ] is the speed in the geographic system, a n =[a n ,a e ,a d ] is the acceleration in the geographic system, t r is the receiver clock error, t v is the receiver clock frequency difference, R M , R N are the curvature radii of the local meridian and meridian respectively, and T is the navigation update period.

[0059] Navigation filtering uses the Kalman filter algorithm. The extended Kalman filter and the unscented Kalman filter are switched according to the navigation state to fuse the IMU data and GNSS measurement data. The state variable is 11 dimensions:

[0060] X=[[δp n ,δv n ,δa n ,δt r ,δt v ]] T

[0061] In the formula, δp n =[δp n ,δp e ,δp d ] is the position error in the geographic system, δv n =[δv n ,δv e ,δv d ] is the velocity error in the geographic system, δa n =[δa n ,δa e ,δa d ] is the acceleration error in the geographic system, δt r is the receiver clock error, δt v is the receiver clock frequency error.

[0062] The vector tracking submodule adopts adaptive bandwidth adjustment technology to achieve stable tracking of weak signals, and realizes fast and effective recovery and high-precision tracking of weak signals through the signal quality control strategy combined with the signal layer and the information layer.

[0063] The navigation synchronization submodule uses the histogram method and NH coding to achieve bit synchronization, and realizes accurate synchronization and analysis of navigation message information through continuous data matching and BCH decoding.

[0064] The navigation solver module obtains observation information by extracting channel correlation values, pseudo-code phases and carrier phase counts in the code loop and carrier loop. Based on the extracted observation information and ephemeris analysis information, it completes high-precision positioning solution through the least squares method and delay correction technology.

[0065] The working process of the device is as follows:

[0066] Step 1: Two active antennas receive wireless signals respectively. The antennas convert the received satellite navigation signals into electrical signals, pass through bandpass filters to filter out potential interference and image signals, and then amplify the signals through low-noise amplifiers. The navigation signals are then output through bandpass filters and enter the receiving RF module through cables.

[0067] Step 2: The receiving RF module performs signal amplification, RF filtering, mixing, IF filtering, automatic gain control and analog-to-digital conversion on the satellite signal, and obtains a four-bit digital IF signal, which is transmitted to the baseband processing module;

[0068] Step 3: The high-precision three-axis accelerometer and three-axis gyroscope in the inertial measurement module respectively collect and measure inertial navigation information such as acceleration and attitude angle, and transmit them to the baseband processing module at a frequency of 10 Hz and a specified protocol;

[0069] Step 4: The inertial navigation information preprocessing submodule of the baseband processing module preprocesses the velocity and acceleration information generated by the inertial navigation module, corrects the scale factor error and installation error of the accelerometer and gyroscope in the IMU, completes self-calibration during the system startup phase to remove the zero bias value, and converts the linear acceleration and angular velocity data generated by the accelerometer and gyroscope in the body coordinate system to the ground-fixed coordinate system;

[0070] Step 5: The signal combining submodule of the baseband processing module combines the two digital intermediate frequency signals transmitted by the receiving RF module, adopts the signal-to-noise ratio weighted selective combining algorithm, performs real-time signal-to-noise ratio measurement on the input signal, and combines the two navigation signals in a weighted manner based on the measured value;

[0071] Step 6: The high dynamic capture submodule of the baseband processing module uses a frequency block search combined with a fast Fourier transform (FFT) to traverse the high dynamic Doppler range, uses a parallel correlator group and a multi-point parallel FFT pipeline mode to quickly search for navigation signals within the frequency block, performs a threshold check on the detected signal, and sends the successfully captured signal frequency and pseudo code phase information to the vector tracking submodule;

[0072] Step 7: The vector tracking submodule of the baseband processing module receives the signal capture parameters of the high dynamic capture submodule and the attitude and velocity information of the inertial navigation information preprocessing submodule; drives the code tracking loop through the carrier frequency, drives the carrier tracking loop update through the carrier acceleration, and dynamically adjusts the carrier loop bandwidth according to the real-time signal-to-noise ratio and Doppler frequency shift information; uses the geographic system as the navigation coordinate system, uses the position, velocity, and acceleration as the navigation state, and uses the Kalman filter algorithm for navigation update; isolates the weak signal channel based on the signal-to-noise ratio estimate, and re-establishes tracking by restoring the lost signal carrier frequency through navigation state update; automatically switches the extended Kalman filter and the unscented Kalman filter to fuse the IMU data and GNSS measurement data according to the navigation state.

[0073] Step 8: The navigation synchronization submodule of the baseband processing module completes the bit synchronization, frame synchronization and message parsing functions of the navigation signal. The bit synchronization is completed using the histogram method and NH coding method, and the frame synchronization is achieved through BCH decoding to ensure that the received navigation message information is accurate. After the synchronization is completed, the navigation message information is parsed.

[0074] Step 9: The navigation solver module of the baseband processing module extracts the observation information of the pseudocode phase and carrier phase from the signal channel, calculates the pseudorange and Doppler frequency shift from the satellite to the receiver; performs delay correction on the pseudorange and time data to compensate for the delay caused by the ionosphere, troposphere and other effects during signal propagation; and uses the least squares method to complete the three-dimensional position, velocity and time offset calculation based on the pseudorange and satellite ephemeris data, time information and correction parameters analyzed by the navigation synchronization submodule.

[0075] In summary, the present invention receives space satellite navigation signals through a high-temperature resistant receiving antenna, converts them into digital intermediate frequency signals through a receiving radio frequency module, and measures the rocket body inertial navigation data through an inertial measurement module. The baseband processing module realizes the combined processing and high-dynamic capture of the navigation signals, and adopts an "open-loop + correction" framework to perform vector tracking of the navigation signals. After completing the navigation message frame and bit synchronization, the message is parsed, and finally the positioning solution is completed to realize the output of the rocket body speed and position information.

[0076] The present invention adopts an INS-assisted vector tracking algorithm and dual-antenna navigation technology. It has the ability to stably track weak navigation signals and quickly recapture them after losing lock. It has the ability to resist high noise and multipath interference, the ability to accurately position at high speeds and in complex postures, and the ability to resist interference in high noise and multipath environments. It can achieve effective navigation and positioning with high continuity and high precision in a high-dynamic arrow-borne environment, and can be applied to navigation environments with high dynamics and complex postures.

Claims

1. A GNSS / INS vector depth combined arrow-borne navigation and positioning device, characterized in that: Including high temperature resistant receiving antenna, receiving RF module, inertial measurement module, and baseband processing module; The high temperature resistant receiving antenna is an active antenna, which is used to convert the space satellite navigation signal into an electrical signal, and output it after pre-selection filtering, low noise amplification, and bandpass filtering; The receiving RF module includes a low noise amplifier unit, a RF filter unit and an RNSS RF unit, wherein the low noise amplifier unit is used to perform low noise amplification on the signal output by the high temperature resistant receiving antenna, the RF filter unit adopts bandpass filtering, and the RNSS RF unit is used to perform mixing, intermediate frequency filtering, automatic gain control and analog-to-digital conversion on the satellite navigation signal, and finally output a 4-bit digital intermediate frequency signal to the baseband processing module; The inertial measurement module includes a high-precision three-axis accelerometer and a three-axis gyroscope, which are used to measure inertial navigation information including speed and acceleration, and output the inertial navigation information to the baseband processing module; The baseband processing module is used to realize navigation signal processing and information resolution.

2. The arrow-borne navigation and positioning device of the GNSS / INS vector depth combination according to claim 1 is characterized in that: The high temperature resistant receiving antennas are two active antennas, and the receiving radio frequency module includes two groups of low noise amplifier units, radio frequency filter units and RNSS radio frequency units, which process the output signal of one high temperature resistant receiving antenna respectively.

3. The arrow-borne navigation and positioning device of the GNSS / INS vector depth combination according to claim 2 is characterized in that: The baseband processing module comprises: The inertial navigation information preprocessing submodule preprocesses the velocity and acceleration information generated by the inertial measurement module, corrects the scale factor error and installation error of the accelerometer and gyroscope in the IMU, completes self-calibration during the system startup phase to remove the zero bias value, and converts the linear acceleration and angular velocity data generated by the accelerometer and gyroscope in the body coordinate system to the ground-fixed coordinate system; The signal combining submodule combines the two digital intermediate frequency signals transmitted by the receiving RF module, adopts the signal-to-noise ratio weighted selective combining algorithm, performs real-time signal-to-noise ratio measurement on the input signal, and combines the two navigation signals in a weighted manner based on the measured value; The high dynamic capture submodule uses frequency block search and fast Fourier transform to traverse the high dynamic Doppler range, uses a parallel correlator group and a multi-point parallel fast Fourier transform pipeline mode to quickly search for navigation signals within the frequency block, performs a threshold check on the detected signal, and sends the successfully captured signal frequency and pseudo code phase information to the vector tracking submodule; The vector tracking submodule receives the signal capture parameters of the high dynamic capture submodule and the attitude and velocity information of the inertial navigation information preprocessing submodule; drives the code tracking loop through the carrier frequency, drives the carrier tracking loop update through the carrier acceleration, and dynamically adjusts the carrier loop bandwidth according to the real-time signal-to-noise ratio and Doppler frequency shift information; uses the geographic system as the navigation coordinate system, uses the position, velocity, and acceleration as the navigation state, and uses the Kalman filter algorithm for navigation update; isolates the weak signal channel based on the signal-to-noise ratio estimate, restores the carrier frequency of the lost signal through the navigation state update, and re-establishes tracking; automatically switches the extended Kalman filter and the unscented Kalman filter to fuse the IMU data and GNSS measurement data according to the navigation state; The navigation synchronization submodule uses the histogram method and NH coding method to complete bit synchronization, and realizes frame synchronization through continuous data matching and BCH decoding. After synchronization is completed, the navigation message information is parsed; The navigation solver module extracts the observation information of pseudocode phase and carrier phase from the signal channel, calculates the pseudorange and Doppler frequency shift from the satellite to the receiver; performs delay correction on the pseudorange and time data to compensate for the delay caused by the ionosphere and troposphere during signal propagation; and uses the least squares method to complete the three-dimensional position, velocity and time offset calculation based on the pseudorange and satellite ephemeris data, time information and correction parameters analyzed by the navigation synchronization submodule.

4. The arrow-borne navigation and positioning device of the GNSS / INS vector depth combination according to claim 3 is characterized in that: In the high dynamic capture submodule, the correlator group correlates the received input sample data and the locally generated signal, obtains the amplitude of the I / Q correlation result, and then performs 128-point pipeline FFT processing; zero values ​​are filled before FFT processing to reduce processing losses; The FFT processing result is compared with the threshold value, and the amplitude value that meets the conditions and the corresponding time domain and frequency domain values ​​are stored in the register.

5. The arrow-borne navigation and positioning device of the GNSS / INS vector depth combination according to claim 3 is characterized in that: The vector tracking submodule converts the carrier frequency into the code frequency to drive the code tracking loop, and drives the carrier tracking loop to update through the carrier acceleration. The calculation formula of the code NCO driving frequency is: In the formula, is the code NCO driving frequency, is the carrier NCO driving frequency, F rf is the nominal frequency of the RF carrier, F co is the code nominal frequency; Carrier NCO driving frequency It reflects the current state of channel open-loop tracking, and calculates the pseudorange ρ￠ and pseudorange rate based on position and velocity. As the expected value of channel tracking, the code phase correction Δτ and carrier drive frequency correction are obtained by difference In the formula, λ co is the code length, λ ca is the carrier wavelength, t v is the receiver clock frequency error.

6. The arrow-borne navigation and positioning device of GNSS / INS vector depth combination according to claim 3 is characterized in that: The vector tracking submodule uses the Kalman filter algorithm to perform navigation updates as follows: Where L is latitude, λ is longitude, h is height, and v is n =[v n ,v e ,v d ] is the speed in the geographic system, a n =[a n ,a e ,a d ] is the acceleration in the geographic system, t r is the receiver clock error, t v is the receiver clock frequency difference, R M , R N are the local meridian and meridian curvature radii, respectively. T is the navigation update cycle. The symbol "^" is the navigation update status mark. The symbol " - " is the status mark before navigation update; Navigation filtering uses the Kalman filter algorithm, switching between extended Kalman filter and unscented Kalman filter according to the navigation state. The state variable is 11 dimensions, as shown below: X=[[δp n ,δv n ,da n ,δt r ,δt v ]] T In the formula, δp n =[δp n ,δp e ,δp d ] is the position error in the geographic system, δv n =[δv n ,δv e ,δv d ] is the velocity error in the geographic system, δa n =[δa n ,δa e ,δa d ] is the acceleration error in the geographic system, δt r is the receiver clock error, δt v is the receiver clock frequency error.

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