Method and system for capturing ultra wide band navigation signal of low earth orbit satellite

Abstract

The invention discloses a method and a system for capturing an ultra-wideband navigation signal of a low-orbit satellite, which are used for solving the technical problem that the existing method for capturing the ultra-wideband navigation signal of the low-orbit satellite is easy to cause that the signal cannot be locked, and finally the capturing success rate is low. The method comprises the following steps: acquiring ka-band low-orbit satellite signals and low-orbit satellite pseudo-random noise codes corresponding to a plurality of low-orbit satellite ultra-wideband navigation signals; generating a complex signal and an original intermediate-frequency signal according to a preset sampling rate, preset skipping time and the ka-band low-orbit satellite signal; constructing a pseudo-code spectrum library based on the pseudo-random noise codes of the low-orbit satellites, and outputting the pseudo-code spectrum library; determining a discrete frequency search sequence based on known intermediate frequency parameters of the original intermediate frequency signal, performing matrix construction in combination with the complex signal and the pseudo code spectrum library, and outputting a three-dimensional result matrix; and capturing and judging the ultra-wideband navigation signals of the low-orbit satellites by adopting the three-dimensional result matrix, and determining a plurality of successfully captured ultra-wideband navigation signals of the low-orbit satellites.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, and in particular to a method and system for acquiring ultra-wideband navigation signals for low-Earth orbit satellites. Background Technology

[0002] Low Earth Orbit (LEO) satellite systems have been widely used in global communications, remote sensing, and navigation in recent years, and their global coverage has provided new possibilities for numerous application scenarios. However, with the rapid development of these satellite systems, LEO satellite signal acquisition technology is also facing increasing challenges.

[0003] Most current research focuses on medium- and high-Earth orbit (MEO) satellites, which have high orbits, relatively slow motion, and small Doppler shifts. In contrast, low-Earth orbit (LEO) satellites, due to their low orbital altitude, faster motion, and increasing use of the Ka-band for high-speed data transmission, exhibit significantly high dynamic and ultra-wideband characteristics in their signal acquisition environment. Traditional signal acquisition methods based on MEO satellites are increasingly revealing serious shortcomings in the high-dynamic, ultra-wideband LEO satellite scenario, failing to meet the real-time, reliability, and efficiency requirements of practical applications. Therefore, researching and developing efficient and robust acquisition techniques suitable for LEO satellite Ka-band ultra-wideband signals has become a critical issue and research hotspot in the field of satellite navigation and communication.

[0004] Existing methods for acquiring ultra-wideband navigation signals from low-Earth orbit (LEO) satellites largely rely on the wideband characteristics of LEO signals. They construct a two-dimensional search space encompassing code phase and carrier frequency, and perform correlation calculations between a local pseudo-random code and the received signal. Successful acquisition is determined when the correlation peak exceeds a preset threshold. However, the Doppler search range of these methods is mostly designed for traditional low-to-mid-frequency bands, making it difficult to cover wide frequency shifts. Furthermore, the frequency search step size is mismatched with the frequency resolution of LEO signals, easily leading to signal lock-on failures and ultimately resulting in a low acquisition success rate. Summary of the Invention

[0005] This invention provides a method and system for acquiring ultra-wideband navigation signals from low-Earth orbit (LEO) satellites, which solves the technical problem that existing LEO satellite LEO satellite LEO satellite acquisition methods are prone to signal lock failure, resulting in a low acquisition success rate.

[0006] The first aspect of this invention provides a method for acquiring ultra-wideband navigation signals from low-Earth orbit satellites, comprising:

[0007] Obtain the pseudo-random noise codes of low-Earth orbit satellites corresponding to Ka-band low-Earth orbit satellite signals and multiple low-Earth orbit satellite ultra-wideband navigation signals;

[0008] Based on the preset sampling rate, preset skip time, and the ka-band low-orbit satellite signal, a complex signal and an original intermediate frequency signal are generated.

[0009] Based on the pseudo-random noise codes of the low-orbit satellites, a pseudo-code spectrum library is constructed and output.

[0010] Based on the known intermediate frequency parameters of the original intermediate frequency signal, a discrete frequency search sequence is determined;

[0011] A matrix is ​​constructed based on the discrete frequency search sequence, the complex signal, and the pseudocode spectrum library, and a three-dimensional result matrix is ​​output.

[0012] The three-dimensional result matrix is ​​used to determine the acquisition of each of the low-Earth orbit satellite ultra-wideband navigation signals, and multiple successfully acquired low-Earth orbit satellite ultra-wideband navigation signals are identified.

[0013] Optionally, the step of generating a complex signal and an original intermediate frequency signal based on a preset sampling rate, a preset skip time, and the ka-band low-Earth orbit satellite signal includes:

[0014] The ka-band low-orbit satellite signal is down-converted to output the original intermediate frequency signal;

[0015] Calculate the number of samples to be skipped based on the preset sampling rate and the preset skip time;

[0016] Based on the number of samples to be skipped, the original intermediate frequency signal is sampled using a file pointer offset operation to determine the I-channel signal data and the Q-channel signal data after skipping the unstable signal portion.

[0017] The I-channel signal data after skipping the unstable signal portion and the Q-channel signal data after skipping the unstable signal portion are merged to generate a complex signal.

[0018] Optionally, the step of constructing a pseudocode spectrum library based on the pseudo-random noise codes of each of the low-Earth orbit satellites and outputting the pseudocode spectrum library includes:

[0019] Based on the satellite serial number associated with each of the low-orbit satellite pseudo-random noise codes, determine the initial binary state of the register corresponding to each of the low-orbit satellite pseudo-random noise codes;

[0020] Perform shift and modulo-2 operations on the binary initial states of each register to output the Gold code sequence corresponding to the pseudo-random noise code of each low-Earth orbit satellite.

[0021] Each Gold code sequence is truncated according to a preset chip length to determine the initial pseudocode sequence corresponding to each Gold code sequence;

[0022] Perform a Fast Fourier Transform on each of the initial pseudocode sequences to generate the pseudocode spectrum corresponding to each of the initial pseudocode sequences;

[0023] Based on the various pseudocode spectra, a pseudocode spectrum library is constructed.

[0024] Optionally, the step of constructing a matrix based on the discrete frequency search sequence, the complex signal, and the pseudocode spectrum library, and outputting a three-dimensional result matrix, includes:

[0025] Based on the known intermediate frequency parameters of the original intermediate frequency signal, a discrete frequency search sequence is determined;

[0026] The complex signal is frequency compensated based on the discrete frequency search sequence to determine the compensated complex signal;

[0027] Perform a Fast Fourier Transform on the compensated complex signal to generate a frequency domain signal;

[0028] Perform complex conjugate operations on each pseudocode spectrum in the pseudocode spectrum library, and output the conjugate spectrum corresponding to each pseudocode spectrum.

[0029] The frequency domain signal is multiplied point by point with each of the conjugate spectra to determine multiple coherent integration results;

[0030] Each coherent integral result is subjected to inverse fast Fourier transform and amplitude extraction in turn to generate time-domain results at multiple frequency points.

[0031] A three-dimensional result matrix is ​​constructed based on the time-domain results of multiple frequency points.

[0032] Optionally, the step of using the three-dimensional result matrix to determine the acquisition of each of the low-Earth orbit satellite ultra-wideband navigation signals, and identifying multiple successfully acquired low-Earth orbit satellite ultra-wideband navigation signals, includes:

[0033] Extract the primary peak value and secondary peak value corresponding to each of the low-Earth orbit satellite ultra-wideband navigation signals from the three-dimensional result matrix, and calculate the peak value ratio corresponding to each of the low-Earth orbit satellite ultra-wideband navigation signals;

[0034] The peak ratios of the ultra-wideband navigation signals of each of the low-orbit satellites are compared with preset ratio thresholds.

[0035] Any low-Earth orbit satellite ultra-wideband navigation signal whose peak ratio is greater than the preset ratio threshold is considered a successfully acquired low-Earth orbit satellite ultra-wideband navigation signal.

[0036] Optionally, the discrete frequency search sequence is specifically:

[0037] ;

[0038] in, For discrete frequency search sequences; The known intermediate frequency parameters of the original intermediate frequency signal represent the initial intermediate frequency of the signal; The maximum frequency of the search; Index for search count, K represents the total number of searches; This represents the frequency step size for the search.

[0039] A second aspect of the present invention provides a low-Earth orbit satellite ultra-wideband navigation signal acquisition system, comprising:

[0040] The acquisition module is used to acquire the pseudo-random noise codes of low-Earth orbit satellites corresponding to the ka-band low-Earth orbit satellite signals and multiple low-Earth orbit satellite ultra-wideband navigation signals;

[0041] According to the module, it is used to generate complex signals and original intermediate frequency signals based on preset sampling rate, preset skip time, and the ka-band low-orbit satellite signals;

[0042] The output module is used to construct a pseudocode spectrum library based on the pseudo-random noise codes of each of the low-orbit satellites and output the pseudocode spectrum library.

[0043] The determination module is used to determine a discrete frequency search sequence based on the known intermediate frequency parameters of the original intermediate frequency signal;

[0044] The construction module is used to construct a matrix based on the discrete frequency search sequence, the complex signal, and the pseudocode spectrum library, and output a three-dimensional result matrix.

[0045] The determination module is used to determine the acquisition of each of the low-orbit satellite ultra-wideband navigation signals based on the three-dimensional result matrix, and to identify multiple successfully acquired low-orbit satellite ultra-wideband navigation signals.

[0046] A computer device provided in a third aspect of the present invention includes a memory and a processor. The memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the low-orbit satellite ultra-wideband navigation signal acquisition method as described in any of the preceding claims.

[0047] The fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, implements the steps of the low-Earth orbit satellite ultra-wideband navigation signal acquisition method as described in any of the preceding claims.

[0048] The fifth aspect of the present invention provides a computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein, when the program instructions are executed by a computer, the computer performs the steps of the low-Earth orbit satellite ultra-wideband navigation signal acquisition method as described in any of the preceding claims.

[0049] As can be seen from the above technical solutions, the present invention has the following advantages:

[0050] The above-described technical solution of the present invention provides a method for acquiring ultra-wideband navigation signals from low-Earth orbit (LEO) satellites. This method involves acquiring LEO satellite signals in the Ka band and corresponding LEO satellite pseudo-random noise codes for multiple LEO satellite LEO satellite LEO satellite LEO signals; generating complex signals and original intermediate frequency (IF) signals based on a preset sampling rate, preset skip time, and the Ka band LEO satellite signals; constructing a pseudo-code spectrum library based on the pseudo-random noise codes of each LEO satellite and outputting the pseudo-code spectrum library; determining a discrete frequency search sequence based on the known IF parameters of the original IF signals; constructing a matrix based on the discrete frequency search sequence, complex signals, and the pseudo-code spectrum library, and outputting a three-dimensional result matrix; using the three-dimensional result matrix to determine the acquisition of each LEO satellite LEO satellite LEO satellite LEO satellite LEO signal, and identifying multiple successfully acquired LEO satellite LEO satellite LEO satellite LEO navigation signals. Based on the above solution, the present invention acquires Ka band LEO satellite signals and generates LEO satellite pseudo-random noise codes for multiple successful acquisitions. The target signal from the low-orbit satellite in the frequency band and the pseudo-random noise code are used to generate a complex signal and the original intermediate frequency signal. Then, relying on the constructed pseudo-code spectrum library to cover a wide range of Doppler frequency shift, the joint search accuracy of code phase and carrier frequency is optimized by combining the three-dimensional result matrix constructed from the above signals. The acquisition determination process is completed through matrix analysis, which avoids the situation in existing methods where the signal cannot be locked due to insufficient Doppler search range and frequency step size mismatch, thereby improving the signal acquisition success rate. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart illustrating the steps of a method for acquiring ultra-wideband navigation signals for low-Earth orbit satellites according to Embodiment 1 of the present invention.

[0053] Figure 2 This is a flowchart illustrating a method for acquiring ultra-wideband navigation signals from low-Earth orbit satellites according to Embodiment 1 of the present invention.

[0054] Figure 3 This is a structural block diagram of a low-orbit satellite ultra-wideband navigation signal acquisition system provided in Embodiment 2 of the present invention. Detailed Implementation

[0055] This invention provides a method and system for acquiring ultra-wideband navigation signals from low-Earth orbit (LEO) satellites, which addresses the technical problem that existing LEO satellite LEO satellite LEO satellite acquisition methods are prone to signal lock failure, ultimately resulting in a low acquisition success rate.

[0056] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0057] Terminology Explanation:

[0058] Ka (K-above) band: refers to a specific frequency range in the radio spectrum, belonging to the microwave band. The frequency range of the Ka band is approximately 20 GHz to 40 GHz.

[0059] Please see Figure 1 , Figure 1 The flowchart illustrates the steps of a method for acquiring ultra-wideband navigation signals from low-orbit satellites, as provided in Embodiment 1 of the present invention.

[0060] This invention provides a method for acquiring ultra-wideband navigation signals from low-Earth orbit satellites, comprising:

[0061] Step 101: Obtain the pseudo-random noise codes of low-Earth orbit satellites corresponding to the ka-band low-Earth orbit satellite signals and multiple low-Earth orbit satellite ultra-wideband navigation signals.

[0062] Ka-band low-Earth orbit (LEO) satellite signals: These refer to signals transmitted by LEO satellites (satellites with low orbital altitudes and high speeds) operating in the Ka band (microwave frequency band in the radio spectrum, ranging from 20 GHz to 40 GHz). Due to the high carrier frequency of the Ka band and the motion characteristics of LEO satellites, these signals exhibit significant high dynamic characteristics and are prone to producing Doppler shifts on the order of ±500 kHz.

[0063] Low Earth Orbit (LEO) satellite ultra-wideband navigation signals refer to ultra-wideband signals (bandwidth ≥ 20MHz) emitted by LEO satellites for navigation purposes. They are characterized by large information capacity, strong resistance to multipath and interference, but due to their wide bandwidth, they also cause problems such as large code phase frequency shift and equivalent noise bandwidth expansion (e.g., a 10-fold increase), posing challenges to signal acquisition.

[0064] It should be noted that each low-Earth orbit (LEO) satellite ultra-wideband navigation signal has a corresponding LEO satellite, thereby obtaining the local pseudo-code sequence (satellite PRN, Pseudo Random Noise) corresponding to the LEO satellite, which is the LEO satellite pseudo-random noise code corresponding to the LEO satellite ultra-wideband navigation signal.

[0065] Step 102: Generate complex signals and original intermediate frequency signals based on preset sampling rate, preset skip time, and ka-band low-orbit satellite signals.

[0066] It should be noted that the process of generating complex signals and raw intermediate frequency (IF) signals based on preset sampling rates, preset skip times, and Ka-band LEO satellite signals is as follows: First, the raw IF signal file corresponding to the Ka-band LEO satellite signal is read. This file contains orthogonal I and Q independent sampling data. Based on the preset sampling rate and preset skip time, the number of unstable samples to be skipped in the early stages (i.e., the product of the preset sampling rate and the preset skip time) is calculated, and these samples are skipped through file pointer offset operations. Then, subsequent valid samples are read to form the raw IF signal without complex processing. Finally, the read I and Q signals are combined into a complex form to obtain the complex signal, which provides the basic input for subsequent signal processing.

[0067] Among them, the I-channel signal, or in-phase signal, is a baseband component obtained after the radio signal is quadratured and demodulated. Its phase is consistent with the phase of the reference carrier (phase difference is 0°) and is used to carry the in-phase information of the signal.

[0068] The Q signal, or Quadrature signal, is another baseband component corresponding to the I signal. Its phase differs from that of the reference carrier by 90° and is used to carry the orthogonal information of the signal.

[0069] Orthogonal I and Q independently sampled data: This refers to data obtained by independently sampling the I and Q signals respectively. The two signals are independent due to their orthogonal phase (90° out of phase), and together they constitute the real (I) and imaginary (Q) parts of a complex signal. In satellite signal processing, this type of data is a common form of raw intermediate frequency (IF) signal. By combining them into a complex signal, it can support subsequent frequency domain processing (such as FFT, frequency compensation, etc.) and serves as the basic input for signal acquisition and tracking.

[0070] Specifically, step 102 may include the following sub-steps S21-S24:

[0071] Step S21: Down-convert the ka-band low-orbit satellite signal to output the original intermediate frequency signal;

[0072] Step S22: Calculate the number of samples to be skipped based on the preset sampling rate and preset skip time;

[0073] Step S23: Based on the number of samples to be skipped, the original intermediate frequency signal is sampled using a file pointer offset operation to determine the I-channel signal data and the Q-channel signal data after skipping the unstable signal portion.

[0074] Step S24: Combine the I-channel signal data after skipping the unstable signal portion and the Q-channel signal data after skipping the unstable signal portion to generate a complex signal.

[0075] It should be noted that the ka-band low-Earth orbit satellite signal is down-converted, and the original intermediate frequency (IF) signal file (i.e., the original IF signal) is read. This signal file is 16-bit integer data and contains two orthogonal independent sampling data.

[0076] Furthermore, to prevent instability in the preceding data in the data file, a preset sampling rate is used. and the preset initial skip time (preset skip time) ), calculate the number of samples to be skipped And skip the previous file pointer offset operation. From a sample, we obtain the I-channel signal data after skipping the unstable signal portion and the Q-channel signal data after skipping the unstable signal portion; where... The number of samples to be skipped is calculated based on the set time for skipping unstable signals and the sampling rate.

[0077] Furthermore, the I-channel signal data after skipping the unstable signal portion and the Q-channel signal data after skipping the unstable signal portion are combined into a complex form, i.e., a complex signal. ,in, The data for the I-channel signal after skipping the unstable signal portion at time t; The Q-channel signal data after skipping the unstable signal portion at time t; It is the imaginary unit.

[0078] Step 103: Construct a pseudocode spectrum library based on the pseudo-random noise codes of each low-orbit satellite and output the pseudocode spectrum library.

[0079] It should be noted that the process of constructing and outputting the pseudocode spectrum library based on the pseudo-random noise codes of each low-Earth orbit satellite is as follows: Based on the PRN number corresponding to each low-Earth orbit satellite, two 14-level linear feedback shift registers are used to perform shifting and modulo-2 operations according to a preset generator polynomial to generate the corresponding Gold code. The required chip length is then truncated to obtain the local pseudo-random noise code sequence (initial pseudocode sequence) for each satellite. Subsequently, a Fast Fourier Transform (FFT) is performed on the pseudocode sequence of each satellite to convert the time-domain pseudocode into a frequency-domain representation. Finally, the frequency-domain results of all satellite pseudocodes are integrated to form a pseudocode spectrum library containing the spectral characteristics of each satellite's pseudocode, providing pre-stored frequency-domain data support for subsequent frequency-domain correlation operations between signals and pseudocodes.

[0080] Specifically, step 103 may include the following sub-steps S31-S35:

[0081] Step S31: Based on the satellite sequence number associated with the pseudo-random noise code of each low-Earth orbit satellite, determine the initial binary state of the register corresponding to the pseudo-random noise code of each low-Earth orbit satellite.

[0082] Step S32: Perform shift and modulo-2 sum operations on the initial binary state of each register to output the Gold code sequence corresponding to the pseudo-random noise code of each low-orbit satellite;

[0083] Step S33: Truncate each Gold code sequence according to the preset chip length to determine the initial pseudo code sequence corresponding to each Gold code sequence;

[0084] Step S34: Perform a fast Fourier transform on each initial pseudocode sequence to generate the pseudocode spectrum corresponding to each initial pseudocode sequence.

[0085] Step S35: Construct a pseudocode spectrum library based on multiple pseudocode spectra.

[0086] It should be noted that, based on the input satellite PRN number (1-168), which is the number corresponding to the pseudo-random noise code of the low-Earth orbit satellite (satellite serial number), two 14-level linear feedback shift registers are used to generate Gold codes (Gold code sequences) according to the generator polynomial through shifting and modulo-2 summation. The initial pseudo-code sequence is then truncated to the required chip length. A Fast Fourier Transform (FFT) is performed on the pseudo-code sequence of each satellite to form a pseudo-code spectrum library.

[0087] Among them, the pseudocode spectrum library is a collection of frequency domain features of all satellite pseudocodes, constructed based on the pseudo-random noise codes corresponding to each low-orbit satellite. It is used to pre-store the frequency domain representation of the pseudocodes and provide data support for subsequent frequency domain correlation operations between signals and pseudocodes.

[0088] Step 104: Determine the discrete frequency search sequence based on the known intermediate frequency parameters of the original intermediate frequency signal.

[0089] It should be noted that, by setting the maximum Doppler frequency shift and the frequency step size, a discrete frequency search sequence is constructed based on the known intermediate frequency parameters of the original intermediate frequency signal:

[0090] ;

[0091] in, For discrete frequency search sequences; The known intermediate frequency parameters of the original intermediate frequency signal represent the initial intermediate frequency of the signal; The maximum frequency for searching, for example, the median frequency is 0. =500kHz means the search will be conducted in the range of [-500kHz, 500kHz]. Index for search count, K is the total number of searches, and the total frequency search points are M = K + 1; This represents the frequency step size for the search.

[0092] Step 105: Construct a matrix based on the discrete frequency search sequence, complex signal, and pseudocode spectrum library, and output a three-dimensional result matrix.

[0093] It should be noted that the process of constructing a matrix based on the discrete frequency search sequence, complex signal, and pseudocode spectrum library to output a three-dimensional result matrix is ​​as follows: Based on the discrete frequency search sequence, the complex signal is sequentially compensated at each frequency point to generate multiple sets of frequency-corrected complex signals; each set of corrected signals is converted to the frequency domain by Fast Fourier Transform (FFT), and multiplied one by one with the pseudocode frequency domain data of each satellite (corresponding to different PRN numbers) in the pseudocode spectrum library, and then converted back to the time domain by Inverse Fast Fourier Transform (IFFT) to obtain the code phase correlation results under different PRNs and different frequency offsets; finally, all results are integrated to construct a three-dimensional result matrix with PRN number (satellite identifier), frequency offset, and code phase as three-dimensional coordinates and correlation amplitude as elements, providing complete data support for peak determination in subsequent signal acquisition.

[0094] Specifically, step 105 includes the following sub-steps S51-S56:

[0095] Step S51: Perform frequency compensation on the complex signal based on the discrete frequency search sequence to determine the compensated complex signal;

[0096] Step S52: Perform a fast Fourier transform on the compensated complex signal to generate a frequency domain signal;

[0097] Step S53: Perform complex conjugate operations on each pseudocode spectrum in the pseudocode spectrum library and output the conjugate spectrum corresponding to each pseudocode spectrum.

[0098] Step S54: Multiply the frequency domain signal with each conjugate spectrum point by point to determine multiple coherent integration results;

[0099] Step S55: Perform inverse fast Fourier transform and amplitude extraction on each coherent integral result in turn to generate time-domain results at multiple frequency points.

[0100] Step S56: Construct a three-dimensional result matrix based on the time-domain results of multiple frequency points.

[0101] It should be noted that multiple coherent integrations are performed across the frequency range, and a parallel frequency search is conducted using the FFT method. Specifically, the entire frequency range is traversed, shifting the signal to different frequencies to eliminate the influence of the k-th hypothetical frequency. This involves frequency compensation of the complex signal based on a discrete frequency search sequence, determining the compensated complex signal, which can be expressed as: ,in, Let t be the compensated complex signal at time t, representing the shifting of the signal to different frequencies; For discrete frequency search sequences; This is the preset sampling rate.

[0102] Furthermore, a Fast Fourier Transform (FFT) is performed on the compensated complex signal to obtain the frequency domain signal. Complex conjugate operations are then performed on the spectra of each pseudocode in the pseudocode spectrum library, outputting the conjugate spectrum corresponding to each pseudocode spectrum. The baseband signal (frequency domain signal) undergoing the FFT is multiplied point-by-point with the conjugate spectrum of the local pseudocode, and multiple coherent integrations are performed at different frequencies to obtain multiple coherent integration results. Inverse Fourier Transform (IFFT) is then performed on the coherent integration results at different frequencies, and the amplitude of each result is extracted to obtain the time-domain correlation results (i.e., the time-domain results at frequency points). A three-dimensional result matrix R is constructed based on all the time-domain correlation results. acq This allows the storage of the relevant amplitude values ​​for all PRNs, frequencies, and code phase points. The three-dimensional result matrix includes the frequencies and code phases of all PRNs and their corresponding amplitudes; that is, it includes the amplitude of each result, the output frequency, code phase point, and satellite number.

[0103] Step 106: Use a three-dimensional result matrix to determine the acquisition of each low-Earth orbit satellite's ultra-wideband navigation signal, and identify multiple successfully acquired low-Earth orbit satellite ultra-wideband navigation signals.

[0104] It should be noted that this invention employs a dual-threshold decision mechanism. A preset ratio threshold is set, and the captured signal is determined based on this threshold. Its code phase offset, carrier frequency, and PRN are recorded, at which point the acquisition phase ends. Specifically, all satellites corresponding to their sequence numbers are traversed. From the three-dimensional result matrix data of each satellite, the maximum amplitude (highest peak) and the second largest amplitude (secondary peak) recorded in the previous step are extracted. A decision threshold of 1.5 is set, and the ratio of the highest peak to the secondary peak for each satellite is calculated. If this ratio is greater than 1.5, the ultra-wideband navigation signal of that satellite is considered successfully acquired. The code phase, carrier frequency, and PRN number corresponding to all successfully acquired satellites are recorded, ultimately yielding multiple successfully acquired low-Earth orbit satellite ultra-wideband navigation signals and their key parameters.

[0105] Specifically, step 106 may include the following sub-steps:

[0106] Step S61: Extract the main peak value and secondary peak value corresponding to each low-Earth orbit satellite ultra-wideband navigation signal from the three-dimensional result matrix, and calculate the peak value ratio corresponding to each low-Earth orbit satellite ultra-wideband navigation signal.

[0107] Step S62: Compare the peak ratio of each low-orbit satellite ultra-wideband navigation signal with a preset ratio threshold.

[0108] Step S63: Take any low-Earth orbit satellite ultra-wideband navigation signal with a peak ratio greater than a preset ratio threshold as the successfully acquired low-Earth orbit satellite ultra-wideband navigation signal.

[0109] It should be noted that, after traversing all satellites with sequence numbers, the maximum and second largest amplitude values ​​recorded in the previous step for each satellite are selected as the highest and second highest peak values, respectively. This means extracting the primary and secondary peak values ​​corresponding to the ultra-wideband navigation signal of each LEO satellite. A preset ratio threshold of 1.5 is set. The ratio of the highest and second highest peak values ​​(peak ratio) of each satellite is compared to 1.5. Satellites with a ratio greater than 1.5 are considered successfully acquired. In other words, any LEO satellite ultra-wideband navigation signal with a peak ratio greater than the preset threshold is considered a successfully acquired LEO satellite ultra-wideband navigation signal. The code phase, carrier frequency, and PRN number record are then obtained for each successfully acquired LEO satellite ultra-wideband navigation signal.

[0110] For comparison of technical effects, existing technologies can be used as a reference. Ultra-wideband signals typically refer to signals with a bandwidth greater than 500MHz. In the field of low-Earth orbit satellite communication and navigation, Ka-band ultra-wideband signals are favored due to their enormous information capacity and resistance to multipath and interference. Compared to traditional narrowband signals, ultra-wideband signals offer higher time resolution and theoretically possess stronger penetration and resistance to frequency-selective fading. However, their ultra-wide spectrum also means that the signal energy is highly dispersed in the frequency domain. At the receiver, this leads to a significant reduction in the signal power spectral density per unit frequency, making the signal more easily submerged in noise background and significantly reducing the receiver's processing gain and signal detection sensitivity. Furthermore, the equivalent noise bandwidth of an ultra-wideband receiver also increases proportionally with the signal bandwidth. Under a fixed detection threshold, the false alarm probability increases with the increase in bandwidth. This results in a large number of noise-induced spurious peaks in the correlation results, making the identification of normal signal peaks extremely difficult and degrading the acquisition performance.

[0111] High dynamic environments are another core challenge in acquiring low-Earth orbit (LEO) satellite signals. The high-speed motion of LEO satellites in the Ka band (center frequency 20.1 GHz) induces extremely significant Doppler shifts. The Doppler shift range of LEO Ka satellite signals can reach ±500 kHz, and the code phase Doppler can reach 2883 Hz. Such large dynamic frequency offsets and code phase Dopplers far exceed the design range of traditional acquisition methods. The classic serial search acquisition method requires testing each possible combination of code phase and carrier frequency. To ensure sufficient detection probability, the frequency search step size is usually set to around 100 Hz. This means that covering a frequency offset range of ±500 kHz requires testing up to 10,000 frequency points, and even ignoring code phase search, the time required for frequency search alone may exceed 10 seconds.

[0112] The serial search acquisition method is the most basic signal acquisition method for Global Navigation Satellite System (GNSS) receivers. Its core principle is to detect the presence of a satellite signal by sequentially traversing a two-dimensional search space (code phase × carrier frequency). Specifically, the receiver first generates a local copy code identical to the target satellite's pseudo-random noise (PRN) code, and simultaneously generates a local carrier signal (containing two orthogonal components: sine and cosine). The input RF signal is down-converted to baseband and then mixed with the local carrier to eliminate Doppler frequency offset effects, followed by correlation with the local PRN code. The correlator output is integrated and cleared to obtain the correlation value. If this value exceeds a preset detection threshold, signal acquisition is considered successful. Otherwise, the code phase or carrier frequency is adjusted, and the next search iteration begins.

[0113] To overcome the low gain problem of the time-domain serial correlation method, a parallel code phase search method is proposed. Its core breakthrough lies in using frequency domain calculations to complete the search for all code phases in one go. This method is based on Fast Fourier Transform (FFT) to perform correlation operations. First, the center frequency offset is estimated in advance. The received digital intermediate frequency signal s[n] is carrier-mixed to eliminate the estimated frequency offset, obtaining the baseband signal. Then, an N-point Fast Fourier Transform (FFT) is performed on the signal to obtain its frequency domain representation. Subsequently, a local PRN code is generated and padded with zeros to a length of N. Then, the FFT of this signal is calculated to obtain the signal, and its conjugate is taken. The signal is then converted back to the time domain using an inverse FFT to obtain the output sequence and the correlation values ​​of all code phases. Finally, peak values ​​exceeding a set threshold are found in the signal, and their positions correspond to the captured code phase offsets, thus completing the signal acquisition process.

[0114] Ultra-wideband (UWB) signals can overcome multipath effects and interference, maintaining high signal quality, especially in complex electromagnetic environments. However, with the continuous expansion of signal bandwidth, noise problems have become increasingly prominent, particularly after the dramatic increase in equivalent noise bandwidth, leading to catastrophic false alarms. In traditional narrowband systems, the signal bandwidth is typically only 2MHz, while in UWB systems, especially when extended to the Ka band, the bandwidth can reach 20MHz. In comparison, the noise bandwidth expands by a factor of 10. This bandwidth expansion not only means increased transmission capacity but also leads to a synchronous increase in system noise power.

[0115] Specifically, when the signal bandwidth expands from traditional narrowband systems to ultra-wideband systems, the equivalent noise bandwidth increases dramatically, leading to a corresponding increase in noise power at the receiver. For correlators in the signal reception process, the noise power at their output increases synchronously with the increase in bandwidth. For example, in traditional narrowband systems, bandwidth and noise power are relatively low, making it easier to extract effective signals in low-noise environments. However, in ultra-wideband systems, the increase in noise power with increasing bandwidth makes the signal-to-noise ratio more complex, ultimately leading to false alarm problems.

[0116] Based on the above, the shortcomings of existing acquisition methods can be roughly divided into four parts: 1. Large Ka-band carrier frequency: The high speed of low-Earth orbit satellites causes the Doppler frequency shift to expand to the ±500kHz level, making it impossible to lock onto many low-Earth orbit satellite signals. 2. The wide bandwidth of the Ka-band ultra-wideband signal leads to a large code phase frequency shift: The gain will decrease when using traditional time-domain correlation methods. 3. The equivalent noise bandwidth introduced by ultra-wideband is expanded by 10 times, resulting in a large number of spurious peaks in the correlation results. The false alarm rate of the fixed threshold detection method will increase at a bandwidth of 20MHz. 4. Low computational efficiency: Traditional frequency-domain parallel code phase acquisition methods need to repeatedly calculate the local pseudo-code FFT for each satellite at each frequency search point, which will increase the computational load.

[0117] For the above issues, please refer to Figure 2 This invention provides a method for acquiring ultra-wideband navigation signals from low-Earth orbit satellites. The method employs parallel code phase analysis to acquire satellite signals, converting the signals to the frequency domain for processing. Furthermore, to avoid repeatedly calculating the local pseudocode FFT at each frequency search point and during the acquisition process of each satellite, the invention pre-calculates and stores the local pseudocode FFT results for all satellites to be acquired. In subsequent acquisition loops, the stored FFT results are directly called for relevant calculations. Simultaneously, this invention introduces a dual-threshold decision method, determining the presence of a signal by analyzing the ratio of the primary peak to the secondary peak, thus improving the reliability of acquisition. In practical applications, when a signal appears, the primary peak usually represents the main characteristic of the signal, while the secondary peak may be caused by noise or interference. By accurately analyzing the ratio between the primary and secondary peaks, the system can more accurately distinguish between valid signals and irrelevant noise, thereby reducing the probability of false alarms and misjudgments.

[0118] Unlike traditional fixed-threshold discrimination methods, the dual-threshold discrimination method proposed in this invention can also adjust the decision threshold according to the noise level. Under different environmental conditions, the decision criterion can be adjusted according to the measured noise level to ensure that signals and noise can still be effectively distinguished even in high-noise environments. This adjustment mechanism not only enhances the adaptability of the algorithm but also enables the method to maintain high detection accuracy and reliability under various environmental conditions.

[0119] In summary, this invention focuses on the acquisition of low-Earth orbit (LEO) satellite navigation signals, filling a research gap in this field. It optimizes for the characteristics of LEO satellites, improving acquisition efficiency and accuracy. This invention employs a parallel code phase method to transfer the signal to the frequency domain for processing. Compared to traditional serial methods, this method significantly improves signal processing speed and accuracy, exhibiting stronger robustness, especially in low signal-to-noise ratio (SNR) environments. Furthermore, to avoid repeatedly calculating the local pseudocode FFT at each frequency search point and during the acquisition process of each satellite, this patent pre-calculates and stores the local pseudocode FFT results for all satellites to be acquired. In subsequent acquisition loops, the stored FFT results are directly called for relevant calculations. In addition, this invention significantly reduces the false alarm rate and improves the system's reliability in signal acquisition through a dual-threshold decision method combined with a mechanism for dynamically adjusting the decision threshold, making it particularly suitable for complex and high-noise environments.

[0120] In this embodiment of the invention, a method for acquiring ultra-wideband navigation signals from low-Earth orbit (LEO) satellites is provided. This method involves acquiring LEO satellite signals in the Ka band and corresponding LEO satellite pseudo-random noise codes for multiple LEO satellite LEO satellite LEO satellite LEO satellite signals; generating complex signals and original intermediate frequency (IF) signals based on a preset sampling rate, preset skip time, and the Ka band LEO satellite signals; constructing a pseudo-code spectrum library based on the pseudo-random noise codes of each LEO satellite and outputting the pseudo-code spectrum library; determining a discrete frequency search sequence based on the known IF parameters of the original IF signals; constructing a matrix based on the discrete frequency search sequence, complex signals, and the pseudo-code spectrum library, and outputting a three-dimensional result matrix; using the three-dimensional result matrix to determine the acquisition of each LEO satellite LEO satellite LEO satellite LEO satellite LEO satellite signal, and identifying multiple successfully acquired LEO satellite ... The target signal from the low-orbit satellite in the frequency band and the pseudo-random noise code are used to generate a complex signal and the original intermediate frequency signal. Then, relying on the constructed pseudo-code spectrum library to cover a wide range of Doppler frequency shift, the joint search accuracy of code phase and carrier frequency is optimized by combining the three-dimensional result matrix constructed from the above signals. The acquisition determination process is completed through matrix analysis, which avoids the situation in existing methods where the signal cannot be locked due to insufficient Doppler search range and frequency step size mismatch, thereby improving the signal acquisition success rate.

[0121] Please see Figure 3 , Figure 3 This is a structural block diagram of a low-orbit satellite ultra-wideband navigation signal acquisition system provided in Embodiment 2 of the present invention.

[0122] This invention provides a low-Earth orbit satellite ultra-wideband navigation signal acquisition system, comprising:

[0123] The acquisition module 301 is used to acquire the pseudo-random noise code of low-Earth orbit satellites corresponding to the ka-band low-Earth orbit satellite signals and multiple low-Earth orbit satellite ultra-wideband navigation signals;

[0124] According to module 302, it is used to generate complex signals and original intermediate frequency signals based on preset sampling rate, preset skip time, and ka-band low-orbit satellite signals;

[0125] Output module 303 is used to construct a pseudocode spectrum library based on the pseudo-random noise codes of various low-orbit satellites and output the pseudocode spectrum library.

[0126] The determination module 304 is used to determine the discrete frequency search sequence based on the known intermediate frequency parameters of the original intermediate frequency signal;

[0127] Module 305 is used to construct a matrix based on discrete frequency search sequences, complex signals, and pseudocode spectrum libraries, and output a three-dimensional result matrix.

[0128] The determination module 306 is used to determine the acquisition of each low-orbit satellite ultra-wideband navigation signal based on the three-dimensional result matrix, and to identify multiple successfully acquired low-orbit satellite ultra-wideband navigation signals.

[0129] Furthermore, according to module 302, it is specifically used for:

[0130] Down-convert the ka-band low-Earth orbit satellite signal to output the original intermediate frequency signal;

[0131] Calculate the number of samples to be skipped based on the preset sampling rate and preset skip time;

[0132] Based on the number of samples to be skipped, the original intermediate frequency signal is sampled using a file pointer offset operation to determine the I-channel signal data and the Q-channel signal data after skipping the unstable signal portion.

[0133] The I-channel signal data after skipping the unstable signal portion and the Q-channel signal data after skipping the unstable signal portion are merged to generate a complex signal.

[0134] Furthermore, the output module 303 is specifically used for:

[0135] Based on the pseudo-random noise codes of each low-Earth orbit satellite, determine the binary initial state of the register corresponding to the pseudo-random noise codes of each low-Earth orbit satellite.

[0136] Perform shift and modulo-2 operations on the initial binary states of each register to output the Gold code sequence corresponding to the pseudo-random noise code of each low-Earth orbit satellite.

[0137] Each Gold code sequence is truncated according to a preset chip length to determine the initial pseudocode sequence corresponding to each Gold code sequence;

[0138] Perform a Fast Fourier Transform on each initial pseudocode sequence to generate the pseudocode spectrum corresponding to each initial pseudocode sequence.

[0139] A pseudocode spectrum library is constructed based on multiple pseudocode spectra.

[0140] Furthermore, module 305 is constructed, specifically for:

[0141] Frequency compensation of complex signals is performed based on discrete frequency search sequences to determine the compensated complex signals.

[0142] Perform a Fast Fourier Transform on the compensated complex signal to generate a frequency domain signal;

[0143] Perform complex conjugate operations on each pseudocode spectrum in the pseudocode spectrum library and output the conjugate spectrum corresponding to each pseudocode spectrum.

[0144] The frequency domain signal is multiplied point by point with each conjugate spectrum to determine multiple coherent integral results;

[0145] Each coherent integral result is subjected to inverse fast Fourier transform and amplitude extraction in turn to generate time-domain results at multiple frequency points.

[0146] A three-dimensional result matrix is ​​constructed based on the time-domain results at multiple frequency points.

[0147] Furthermore, a three-dimensional result matrix is ​​used to determine the acquisition of each low-Earth orbit (LEO) satellite's ultra-wideband (UWB) navigation signal, identifying several successfully acquired LEO satellite UWB navigation signals, including:

[0148] Extract the main peak value and secondary peak value corresponding to each low-Earth orbit satellite ultra-wideband navigation signal from the three-dimensional result matrix, and calculate the peak value ratio corresponding to each low-Earth orbit satellite ultra-wideband navigation signal.

[0149] Compare the peak ratios of the ultra-wideband navigation signals of each low-orbit satellite with preset ratio thresholds;

[0150] The low-Earth orbit satellite ultra-wideband navigation signal corresponding to any peak ratio greater than a preset ratio threshold is taken as the successfully acquired low-Earth orbit satellite ultra-wideband navigation signal.

[0151] Furthermore, the discrete frequency search sequence is as follows:

[0152] ;

[0153] in, For discrete frequency search sequences; The known intermediate frequency parameters of the original intermediate frequency signal represent the initial intermediate frequency of the signal; The maximum frequency of the search; Index for search count, K represents the total number of searches; This represents the frequency step size for the search.

[0154] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the system and modules described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0155] This invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program; when the computer program is executed by the processor, the processor performs the steps of the low-orbit satellite ultra-wideband navigation signal acquisition method as described in any of the above embodiments.

[0156] This invention also provides a computer-readable storage medium storing a computer program / instructions thereon, which, when executed by a processor, implements the steps of the low-Earth orbit satellite ultra-wideband navigation signal acquisition method as described in any of the above embodiments.

[0157] This invention also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the low-Earth orbit satellite ultra-wideband navigation signal acquisition method as described in any of the above embodiments.

[0158] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0159] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0160] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for acquiring ultra-wideband navigation signals from low-Earth orbit satellites, characterized in that, include: Obtain the pseudo-random noise codes of low-Earth orbit satellites corresponding to Ka-band low-Earth orbit satellite signals and multiple low-Earth orbit satellite ultra-wideband navigation signals; Based on the preset sampling rate, preset skip time, and the ka-band low-orbit satellite signal, a complex signal and an original intermediate frequency signal are generated. Based on the pseudo-random noise codes of the low-orbit satellites, a pseudo-code spectrum library is constructed and output. Based on the known intermediate frequency parameters of the original intermediate frequency signal, a discrete frequency search sequence is determined; A matrix is ​​constructed based on the discrete frequency search sequence, the complex signal, and the pseudocode spectrum library, and a three-dimensional result matrix is ​​output. The three-dimensional result matrix is ​​used to determine the acquisition of each of the low-Earth orbit satellite ultra-wideband navigation signals, and multiple successfully acquired low-Earth orbit satellite ultra-wideband navigation signals are identified.

2. The method for acquiring ultra-wideband navigation signals from low-orbit satellites according to claim 1, characterized in that, The process of generating a complex signal and a raw intermediate frequency signal based on a preset sampling rate, a preset skip time, and the ka-band low-Earth orbit satellite signal includes: The ka-band low-orbit satellite signal is down-converted to output the original intermediate frequency signal; Calculate the number of samples to be skipped based on the preset sampling rate and the preset skip time; Based on the number of samples to be skipped, the original intermediate frequency signal is sampled using a file pointer offset operation to determine the I-channel signal data and the Q-channel signal data after skipping the unstable signal portion. The I-channel signal data after skipping the unstable signal portion and the Q-channel signal data after skipping the unstable signal portion are merged to generate a complex signal.

3. The method for acquiring ultra-wideband navigation signals from low-Earth orbit satellites according to claim 1, characterized in that, The process of constructing a pseudocode spectrum library based on the pseudo-random noise codes of each of the aforementioned low-Earth orbit satellites, and outputting the pseudocode spectrum library, includes: Based on the satellite serial number associated with each of the low-orbit satellite pseudo-random noise codes, determine the initial binary state of the register corresponding to each of the low-orbit satellite pseudo-random noise codes; Perform shift and modulo-2 operations on the binary initial states of each register to output the Gold code sequence corresponding to the pseudo-random noise code of each low-Earth orbit satellite. Each Gold code sequence is truncated according to a preset chip length to determine the initial pseudocode sequence corresponding to each Gold code sequence; Perform a Fast Fourier Transform on each of the initial pseudocode sequences to generate the pseudocode spectrum corresponding to each of the initial pseudocode sequences; Based on the various pseudocode spectra, a pseudocode spectrum library is constructed.

4. The method for acquiring ultra-wideband navigation signals from low-Earth orbit satellites according to claim 1, characterized in that, The step of constructing a matrix based on the discrete frequency search sequence, the complex signal, and the pseudocode spectrum library, and outputting a three-dimensional result matrix, includes: The complex signal is frequency compensated based on the discrete frequency search sequence to determine the compensated complex signal; Perform a Fast Fourier Transform on the compensated complex signal to generate a frequency domain signal; Perform complex conjugate operations on each pseudocode spectrum in the pseudocode spectrum library, and output the conjugate spectrum corresponding to each pseudocode spectrum. The frequency domain signal is multiplied point by point with each of the conjugate spectra to determine multiple coherent integration results; Each coherent integral result is subjected to inverse fast Fourier transform and amplitude extraction in turn to generate time-domain results at multiple frequency points. A three-dimensional result matrix is ​​constructed based on the time-domain results of multiple frequency points.

5. The method for acquiring ultra-wideband navigation signals from low-Earth orbit satellites according to claim 1, characterized in that, The method of using the three-dimensional result matrix to acquire and determine the ultra-wideband navigation signals of each low-Earth orbit satellite, and identifying multiple successfully acquired ultra-wideband navigation signals of low-Earth orbit satellites, including: Extract the primary peak value and secondary peak value corresponding to each of the low-Earth orbit satellite ultra-wideband navigation signals from the three-dimensional result matrix, and calculate the peak value ratio corresponding to each of the low-Earth orbit satellite ultra-wideband navigation signals; The peak ratios of the ultra-wideband navigation signals of each of the low-orbit satellites are compared with preset ratio thresholds. Any low-Earth orbit satellite ultra-wideband navigation signal whose peak ratio is greater than the preset ratio threshold is considered a successfully acquired low-Earth orbit satellite ultra-wideband navigation signal.

6. The method for acquiring ultra-wideband navigation signals for low-Earth orbit satellites according to claim 4, characterized in that, The discrete frequency search sequence is specifically as follows: ； in, For discrete frequency search sequences; The known intermediate frequency parameters of the original intermediate frequency signal represent the initial intermediate frequency of the signal; The maximum frequency of the search; An index for the number of searches. K represents the total number of searches; This represents the frequency step size for the search.

7. A low-Earth orbit satellite ultra-wideband navigation signal acquisition system, characterized in that, include: The acquisition module is used to acquire the pseudo-random noise codes of low-Earth orbit satellites corresponding to the ka-band low-Earth orbit satellite signals and multiple low-Earth orbit satellite ultra-wideband navigation signals; According to the module, it is used to generate complex signals and original intermediate frequency signals based on preset sampling rate, preset skip time, and the ka-band low-orbit satellite signals; The output module is used to construct a pseudocode spectrum library based on the pseudo-random noise codes of each of the low-orbit satellites and output the pseudocode spectrum library. The determination module is used to determine a discrete frequency search sequence based on the known intermediate frequency parameters of the original intermediate frequency signal; The construction module is used to construct a matrix based on the discrete frequency search sequence, the complex signal, and the pseudocode spectrum library, and output a three-dimensional result matrix. The determination module is used to determine the acquisition of each of the low-orbit satellite ultra-wideband navigation signals based on the three-dimensional result matrix, and to identify multiple successfully acquired low-orbit satellite ultra-wideband navigation signals.

8. A computer device, characterized in that, The system includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the low-Earth orbit satellite ultra-wideband navigation signal acquisition method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the low-orbit satellite ultra-wideband navigation signal acquisition method as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, wherein when the program instructions are executed by a computer, the computer performs the low-orbit satellite ultra-wideband navigation signal acquisition method as described in any one of claims 1-6.

Images