Satellite signal searching method and device, nonvolatile storage medium and electronic device

Abstract

The application discloses a satellite signal searching method and device, a nonvolatile storage medium and an electronic device. The method comprises the following steps: after a target array element in a satellite antenna array receives a satellite signal to be processed, performing correlation operation on the satellite signal to be processed by a binary offset carrier code correlation branch in the target array element, performing time integration and sampling processing, obtaining a first processing result, and determining signal peak value information of the satellite signal to be processed; performing dimension reduction processing on the first processing result according to the signal peak value information by an analog-to-digital converter in the target array element, obtaining a second processing result; and reducing the dimension of the second processing result corresponding to each array element by a space-time adaptive processing module in the satellite antenna array, suppressing wideband interference in the second processing result, and obtaining a search signal. The application solves the technical problem of low search efficiency caused by high search frequency and large calculation amount of the traditional technology when searching for a satellite signal.

Description

Technical Field

[0001] The present application relates to satellite communication technology, and more specifically, to a satellite signal search method, device, non-volatile storage medium, and electronic device. Background Art

[0002] In recent years, satellite communication technology has rapidly developed and been widely adopted worldwide, becoming a crucial tool in several fields. For example, in emergency communications, when disasters such as floods and earthquakes render traditional communication methods unavailable, satellite communication is a highly effective solution. However, satellite communication requires the assistance of multiple satellites to achieve real-time communication. The speed of satellite signal search directly impacts the response time and accuracy of equipment. Therefore, how to quickly search for satellites at different angles, reduce search times, and meet the communication needs of specialized scenarios are pressing challenges facing satellite communication technology.

[0003] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0004] The embodiments of the present application provide a satellite signal search method, device, non-volatile storage medium, and electronic device to at least solve the technical problem of low search efficiency caused by the high number of searches and large amount of calculation when searching for satellite signals in traditional technologies.

[0005] According to one aspect of an embodiment of the present application, a satellite signal search method is provided, comprising: after a target array element in a satellite antenna array receives a satellite signal to be processed, performing correlation operations, time integration, and sampling processing on the satellite signal to be processed through a binary offset carrier code correlation branch in the target array element to obtain a first processing result and determine signal peak information of the satellite signal to be processed, wherein the target array element is any array element in the satellite antenna array; performing dimensionality reduction processing on the first processing result based on the signal peak information through an analog-to-digital converter in the target array element to obtain a second processing result; reducing the dimension of the second processing result corresponding to each array element through a space-time adaptive processing module in the satellite antenna array and suppressing broadband interference in the second processing result to obtain a search signal, wherein the search signal is used to determine the communication satellite that sends the satellite signal to be processed.

[0006] Optionally, before processing the signal to be processed by the binary offset carrier code correlation branch in the target array element, the method further includes: performing time-domain filtering processing on the satellite signal to be processed by an N-order finite impulse response filter set in the target array element, and using the satellite signal to be processed after the time-domain filtering processing as an input signal of the binary offset carrier code correlation branch, where N is an arbitrary positive integer.

[0007] Optionally, processing the signal to be processed by the binary offset carrier code correlation branch in the target array element includes: determining a digital intermediate frequency signal in the satellite signal to be processed, wherein the frequency of the digital intermediate frequency signal is within a preset frequency value range; generating a local carrier signal and a local pseudo code by a carrier controlled oscillator in the binary offset carrier code correlation branch, and performing sub-wave modulation on the local pseudo code to obtain a local binary offset carrier code, wherein the local carrier signal includes two signal components, namely, in-phase and orthogonal signals; performing a correlation operation on the digital intermediate frequency signal, the local binary offset carrier code, and the local pseudo code to obtain a correlation operation result, and performing time integration and sampling processing on the correlation operation result to obtain a first processing result.

[0008] Optionally, the digital intermediate frequency signal is correlated with the local binary offset carrier code and the local pseudo code to obtain a correlation operation result, and the correlation operation result is time-integrated and sampled to obtain a first processing result, including: correlating the digital intermediate frequency signal with the local binary offset carrier code to obtain a first correlation operation result; correlating the digital intermediate frequency signal with the local pseudo code to obtain a second correlation operation result; performing integral sampling processing on the first correlation operation result to obtain a first sampling result, and performing integral sampling processing on the second correlation operation result to obtain a second sampling result, wherein the first sampling result and the second sampling result are the first processing results.

[0009] Optionally, after performing integral sampling processing on the first correlation operation result to obtain a first sampling result, and performing integral sampling processing on the second correlation operation result to obtain a second sampling result, the method further includes: performing a modulo square operation on the first sampling result to obtain a first signal strength value, wherein the first signal strength value is used to reflect the degree of matching between the binary offset carrier code in the digital intermediate frequency signal and the local binary offset carrier code; performing a modulo square operation on the second sampling result to obtain a second signal strength value, wherein the second signal strength value is used to reflect the degree of matching between the binary offset carrier code in the digital intermediate frequency signal and the local pseudo code; determining the difference between the first signal strength value and the second signal strength value, and determining the signal peak information based on the difference, wherein the signal peak information includes the frequency value range of the local carrier signal when the difference value is the peak value, and the phase value range of the local pseudo code.

[0010] Optionally, performing dimensionality reduction processing on the first processing result based on signal peak information by an analog-to-digital converter in a target array element to obtain a second processing result includes: performing multiple orthogonal projection decompositions on the first processing result to obtain the second processing result, wherein the second processing result includes a covariance matrix, and the dimension of the covariance matrix is ​​lower than the dimension of the first processing result.

[0011] Optionally, the dimension of the second processing result corresponding to each array element is reduced by the space-time adaptive processing module in the satellite antenna array, and the broadband interference in the second processing result is suppressed to obtain the search signal, including: performing dimensionality reduction processing on the second processing result by the dimensionality reduction multi-scale network waveform unit in the space-time adaptive processing module to obtain a dimensionality reduction processing result; performing interference suppression processing on the dimensionality reduction processing result by the multi-scale network waveform filter in the space-time adaptive processing module to obtain an interference suppression processing result; determining the space-time two-dimensional weight vector and the minimum variance distortion-free response optimization equation based on the interference suppression processing result, and performing a directional iterative search based on the space-time two-dimensional weight vector and the minimum variance distortion-free response optimization equation to obtain the search signal.

[0012] According to another aspect of an embodiment of the present application, a satellite signal search device is also provided, including: a first processing module, used to perform correlation operations, time integration and sampling processing on the satellite signal to be processed through the binary offset carrier code correlation branch in the target array element after the target array element in the satellite antenna array receives the satellite signal to be processed, to obtain a first processing result and determine the signal peak information of the satellite signal to be processed, wherein the target array element is any array element in the satellite antenna array; a second processing module, used to perform dimensionality reduction processing on the first processing result according to the signal peak information through the analog-to-digital converter in the target array element, to obtain a second processing result; a third processing module, used to reduce the dimension of the second processing result corresponding to each array element through the space-time adaptive processing module in the satellite antenna array and suppress broadband interference in the second processing result, to obtain a search signal, wherein the search signal is used to determine the communication satellite that sends the satellite signal to be processed.

[0013] According to another aspect of an embodiment of the present application, a non-volatile storage medium is provided, in which a program is stored. When the program is executed, the device where the non-volatile storage medium is located is controlled to execute a satellite signal search method.

[0014] According to another aspect of an embodiment of the present application, an electronic device is provided, including: a memory and a processor, wherein the processor is configured to run a program stored in the memory, wherein the satellite signal search method is executed when the program is run.

[0015] According to another aspect of an embodiment of the present application, a computer program product is provided, including a computer program, which implements a satellite signal search method when executed by a processor.

[0016] In an embodiment of the present application, after a target element in a satellite antenna array receives a satellite signal to be processed, a binary offset carrier code correlation branch in the target element performs correlation operations, time integration, and sampling on the satellite signal to be processed to obtain a first processing result and determine signal peak information of the satellite signal to be processed. The target element is any element in the satellite antenna array. An analog-to-digital converter in the target element performs dimensionality reduction processing on the first processing result based on the signal peak information to obtain a second processing result. A space-time adaptive processing module in the satellite antenna array reduces the dimension of the second processing result corresponding to each element and suppresses broadband interference in the second processing result to obtain a search signal. The search signal is used to determine the communication satellite transmitting the satellite signal to be processed. By introducing a Fourier transform in the one-dimensional Doppler frequency, the search of multiple frequencies is optimized into a single search, and the dimensionality reduction processing of the satellite signal data is performed, thereby reducing the search computational complexity and achieving the technical effect of improving search efficiency. This solves the technical problem of low search efficiency caused by the high number of searches and large computational complexity in traditional satellite signal searching. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 This is a schematic diagram of the structure of a computer terminal (mobile device) provided according to an embodiment of the present application;

[0019] Figure 2 1 is a schematic diagram of a framework of an optional satellite signal search system provided according to an embodiment of the present application;

[0020] Figure 3 This is a schematic diagram of an optional satellite search process provided according to an embodiment of the present application;

[0021] Figure 4 1 is a schematic diagram of an optional BOC code related branch provided according to an embodiment of the present application;

[0022] Figure 5 1 is a flow chart of a satellite signal search method provided in accordance with an embodiment of the present application;

[0023] Figure 6 is a schematic diagram of the structure of an optional MSNWF provided according to an embodiment of the present application;

[0024] Figure 7 2 is a schematic structural diagram of a satellite signal search device provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] In the related art, the search for satellite signals involves many searches, high data latitude, and complex calculations, resulting in low search efficiency. To address this problem, the present application provides a related solution, which is described in detail below.

[0028] According to an embodiment of the present application, a method embodiment of a satellite signal search method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0029] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 FIG1 shows a hardware structure block diagram of a computer terminal for implementing a satellite signal search method. Figure 1As shown, the computer terminal 10 may include one or more (illustrated as 102a, 102b, ..., 102n in the figure) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission module 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It will be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0030] It should be noted that the one or more processors 102 and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry." The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuitry may be a single, independent processing module, or may be incorporated in whole or in part into any of the other components of the computer terminal 10. As described in the embodiments of the present application, the data processing circuitry serves as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0031] Memory 104 can be used to store software programs and modules for application software, such as the program instructions / data storage device corresponding to the satellite signal search method in the embodiments of the present application. Processor 102 executes the software programs and modules stored in memory 104 to perform various functional applications and data processing, thereby implementing the satellite signal search method for the aforementioned application. Memory 104 can include high-speed random access memory (RAM) and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 104 can further include memory remotely located from processor 102, which can be connected to computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0032] The transmission device 106 is configured to receive or transmit data via a network. A specific example of the aforementioned network may include a wireless network provided by the communications provider of the computer terminal 10. In one embodiment, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission device 106 may be a radio frequency (RF) module, which is configured to communicate with the Internet wirelessly.

[0033] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 .

[0034] In some optional embodiments of the present application, the framework of the satellite signal search system is as follows: Figure 2 As shown in the figure, the process of satellite search based on this system is as follows Figure 3 As shown in the figure: the antenna array receives satellite signals, and the received signals are filtered in the time domain by LNA (low noise amplifier) ​​and RF module (radio frequency module). The peak value of the input information is detected in the BOC (binary offset carrier) code correlation branch. The framework of the BOC code correlation branch is as follows Figure 4 As shown, after peak detection, the data is input into the A / D (analog-to-digital) module for dimensionality reduction processing, and the search signal is output in the STAP module.

[0035] In the above operating environment, the embodiment of the present application provides a satellite signal search method, such as Figure 5 As shown, the method includes the following steps:

[0036] Step S502: After a target element in the satellite antenna array receives a satellite signal to be processed, a correlation operation, time integration, and sampling processing are performed on the satellite signal to be processed via a binary offset carrier code correlation branch in the target element to obtain a first processing result and determine signal peak information of the satellite signal to be processed. The target element is any element in the satellite antenna array.

[0037] In some optional embodiments of the present application, before performing correlation operation, time integration, and sampling processing on the satellite signal to be processed through the binary offset carrier code correlation branch in the target array element, the process further includes performing time domain filtering processing on the satellite signal to be processed through an N-order finite impulse response filter set in the target array element, and using the satellite signal to be processed after the time domain filtering processing as the input signal of the binary offset carrier code correlation branch, where N is an arbitrary positive integer.

[0038] Optionally, the antenna array is provided with M array elements, and each array element is provided with an N-order FIR (Finite Impulse Response) filter to perform time domain filtering on the received satellite signal. This step is to eliminate noise and unnecessary frequency band interference. The processed signal is used as the input of the BOC code correlation branch. After the processing is completed, it is used as the input information of the BOC code correlation branch (i.e., the binary offset carrier code correlation branch).

[0039] In some optional embodiments of the present application, a correlation operation is performed on the satellite signal to be processed through a binary offset carrier code correlation branch in the target array element, and the time integration and sampling processing includes determining a digital intermediate frequency signal in the satellite signal to be processed, wherein the frequency of the digital intermediate frequency signal is within a preset frequency value range; generating a local carrier signal and a local pseudo code through a carrier controlled oscillator in the binary offset carrier code correlation branch, and performing sub-wave modulation on the local pseudo code to obtain a local binary offset carrier code, wherein the local carrier signal includes two signal components of in-phase and orthogonal phase; performing a correlation operation on the digital intermediate frequency signal, the local binary offset carrier code, and the local pseudo code to obtain a correlation operation result, and performing time integration and sampling processing on the correlation operation result to obtain a first processing result.

[0040] Optionally, in an antenna array having M array elements, there are also M BOC code related branches. For any branch, the digital intermediate frequency signal in the input information is represented as follows in the BOC code related branch:

[0041]

[0042] Where c(t) and χ(t) represent the modulation pseudo code and modulated subcarrier in the signal, respectively, τ i (t) represents the propagation phase delay, θ i (t) is the carrier phase, t in this context represents the change in time, and i represents different code phases, that is, different code words.

[0043] In some optional embodiments of the present application, a correlation operation is performed on the digital intermediate frequency signal with a local binary offset carrier code and a local pseudo code to obtain a correlation operation result, and the correlation operation result is time-integrated and sampled to obtain a first processing result, including: performing a correlation operation on the digital intermediate frequency signal with a local binary offset carrier code to obtain a first correlation operation result; performing a correlation operation on the digital intermediate frequency signal with a local pseudo code to obtain a second correlation operation result; performing integral sampling processing on the first correlation operation result to obtain a first sampling result, and performing integral sampling processing on the second correlation operation result to obtain a second sampling result, wherein the first sampling result and the second sampling result are the first processing results.

[0044] Optionally, the digital intermediate frequency signal in the input information is mixed with the carrier NCO (Numerically Controlled Oscillator) and then correlated with the local BOC code. The carrier NCO here is used to control the generation of the local carrier Including two signal components of in-phase and orthogonal, θ o (t) is the output carrier phase, j represents the imaginary unit. The code NOC is used to control the generation of the local pseudo code c(to(t)) and the local BOC code c(t-τ o (t))χ(t-τ o (t)), τ o (t) represents the estimation of the code phase delay of the input signal. After the above calculation, the result is expressed as

[0045] w1(t)=2c(t-τ i (t))c(tr o (t))χ(t-τ i (t))χ(t-τ o (t))·cosθ i (t)(cosθ i (t)+jsinθ o (t))

[0046] =c(t-τ i (t))c(t-τ o (t))χ(t-τ i (t))χ(t-τ o (t))·((cosθ e (t)-cos(θ i (t)+θ o (t)))+j(sinθ e (t)+sin(θ i (t)+θ o (t))))

[0047] Among them, θ e (t) = θ i (t)-θ o (t), w1(t) represents the local power spectrum density of the signal. After integrating for a time period of T, the integration result is sampled to obtain

[0048]

[0049] R BOC / BOC (τ) is the BOC code autocorrelation function, τ e (t) = τ i (t)-τ o (t), we (t) = w i (t)-w o (t), w i (t) and w o (t) are the signal carrier and local carrier angular frequencies, Indicates the mean phase difference between the signal carrier and the local carrier, n is an integer representing the number of discrete sampling points, and TR is a constant representing the integral value of the BOC code autocorrelation function per unit time. BOC / BOC The expression of (τ) is

[0050]

[0051] Since the normalized amplitude-frequency response of the M-point FFT (Fast Fourier Transform) is:

[0052]

[0053] Among them, w is a variable representing the discretized frequency value, and k is an integer representing the discretized angle value. Therefore, the result of normalized FFT can be expressed as:

[0054]

[0055] Where L is the coefficient in the discrete Fourier transform (DFT), which is used to convert the time domain signal into the frequency domain signal.

[0056] The FFT transform converts the signal to the frequency domain, simultaneously processing multiple frequency components to achieve rapid Doppler frequency search. Specifically, the previously required search of 128 frequency points is now completed in a single pass. The Fourier transform processes the input signal in the frequency domain, optimizing the Doppler frequency search from a point-by-point frequency search to a simultaneous search of multiple frequency components in the frequency domain.

[0057] In some optional embodiments of the present application, after performing integral sampling processing on the first correlation operation result to obtain a first sampling result, and performing integral sampling processing on the second correlation operation result to obtain a second sampling result, the method further includes: performing a modulo square operation on the first sampling result to obtain a first signal strength value, wherein the first signal strength value is used to reflect the degree of matching between the binary offset carrier code in the digital intermediate frequency signal and the local binary offset carrier code; performing a modulo square operation on the second sampling result to obtain a second signal strength value, wherein the second signal strength value is used to reflect the degree of matching between the binary offset carrier code in the digital intermediate frequency signal and the local pseudo code; determining the difference between the first signal strength value and the second signal strength value, and determining the signal peak information based on the difference, wherein the signal peak information includes the frequency value range of the local carrier signal when the difference value is the peak value, and the phase value range of the local pseudo code.

[0058] Optionally, square S1(k) modulo to obtain

[0059]

[0060] The pseudo-code related branches have similar results:

[0061]

[0062] Among them, R BOC / PRN (τ) is the cross-correlation function between BOC code and pseudo code, and the expression of BOC / PRN(τ) is

[0063]

[0064] Optionally, during code phase calculation, a parallel correlator is used to search for code phases. The correlator compares the code phase with the local pseudocode, and parallel processing is used to simultaneously search for multiple code phases. Specifically, 100 parallel correlators are used to search 100 code phases simultaneously in one dimension. The parallel correlator's purpose is to process multiple pseudocode phases simultaneously through parallel computing, thereby accelerating the search.

[0065] Subtract V1 from V2 to get the signal peak value:

[0066]

[0067] in, β is a parameter that adjusts the size of the negative peak. The larger β is, the larger the negative peak of the ASPeCT correlation function is. Usually, β = 1 is suitable. Since the peaks of the ASPeCT correlation function and the sinc function appear at τ e and w eTherefore, V will have the maximum peak value only when the local replica carrier frequency is close to the intermediate frequency signal frequency and the local replica pseudo code phase is close to the intermediate frequency signal code phase.

[0068] Step S504: performing dimensionality reduction processing on the first processing result according to the signal peak information by an analog-to-digital converter in the target array element to obtain a second processing result, wherein the dimensionality reduction processing on the first processing result includes performing orthogonal projection decomposition on the result;

[0069] In some optional embodiments of the present application, performing dimensionality reduction processing on the first processing result based on signal peak information by an analog-to-digital converter in a target array element to obtain a second processing result includes performing multiple orthogonal projection decompositions on the first processing result to obtain the second processing result, wherein the second processing result includes a covariance matrix, and the dimension of the covariance matrix is ​​lower than the dimension of the first processing result.

[0070] After peak detection, the information is transmitted to the A / D module for dimensionality reduction. Here, the dimensionality reduction MSNW (Multi-stage Nested Wiener Filter) is used to determine the interference subspace. The input data is subjected to multiple orthogonal projection decompositions. Each orthogonal decomposition yields two subspaces: one parallel to the cross-correlation vector between the desired signal and the previous input data, and the other orthogonal to this subspace. The same decomposition is then performed on the subspace orthogonal to the cross-correlation vector, and this decomposition continues step by step. After D (≤MN) decompositions, the input data is pre-filtered with an MN×D-dimensional matrix T. This compresses the input data from MN dimensions to D dimensions, and the corresponding covariance matrix is ​​also compressed to D×D dimensions. All subsequent processing can be performed on a lower dimension, thereby reducing the computational complexity of the algorithm and improving its real-time performance. The formula used for dimensionality reduction is:

[0071]

[0072] Where hi represents the i-th stage matched filter, is the normalized vector of the cross-correlation between the previous stage desired signal and the input data, is the signal component, and H represents the transfer function of a filter.

[0073] By formula derivation, it can be seen that the subspace spanned by the matched filters at each level of the multi-level nested Wiener filtering satisfies:

[0074] Φ J =span{h1,h2,...,h D}=span{e1,e2,...,e D}

[0075] U J={e1,e2,...,e D} represents the interference signal subspace, let A J =span{h1,h2,...,h D QR decomposition can be used to solve the orthogonal basis vectors of the AJ null space. AJ = QU, where the column orthogonal matrix Q is of MN×MN dimensions and the upper triangular matrix U is of MN×D dimensions. Since AJ is a column full rank matrix, let the column vector of the matrix Q be expressed as Q = [q1,q2,...,q MN ],So

[0076] Φ J =span{q1,q2,...,q D}

[0077] Since the matrix Q is an orthogonal matrix, the space spanned by its last MN-D column vectors is orthogonal to the space spanned by the first D vectors. Therefore, these MN-D orthogonal vectors can be used as the orthogonal basis vectors of AJ, and their matrix form can be expressed as:

[0078] H=[q D+1 ,q D+2 ,...,q MN ]

[0079] After obtaining MN-D orthogonal basis vectors, we need to obtain the space-time two-dimensional weight vector w(MN×1 dimension) in the null space of AJ, d=[d1,d2,...,dMN-D]T, and perform linear combination of the orthogonal basis to obtain:

[0080] w=H[d1,d2,...,d MN－D ] T =Hd

[0081] If the beam is required to have the maximum gain in the direction of the desired signal, then w=a(θ0,f c ), that is, Hd=a(θ0,f c ), θ0 is the direction of the satellite signal, f c is the carrier frequency of the satellite signal. The coefficient H is an overdetermined equation with full rank, so the vector d can be obtained by the least squares method (LS)

[0082] d=(H H H) -1 H H a(θ0,f c )

[0083] Substitute into the formula w=H[d1,d2,...,d MN－D ] T =Hd, we can get the final weight vector

[0084] w=H(HH H) -1 H H a(θ0,f c )

[0085] Step S506: Reduce the dimension of the second processing result corresponding to each array element and suppress broadband interference in the second processing result through the space-time adaptive processing module in the satellite antenna array to obtain a search signal, wherein the search signal is used to determine the communication satellite that sends the satellite signal to be processed.

[0086] In some optional embodiments of the present application, the dimension of the second processing result corresponding to each array element is reduced by a space-time adaptive processing module in the satellite antenna array and broadband interference in the second processing result is suppressed to obtain a search signal, including: performing dimensionality reduction processing on the second processing result by a dimensionality reduction multi-scale network waveform unit in the space-time adaptive processing module to obtain a dimensionality reduction processing result; performing interference suppression processing on the dimensionality reduction processing result by a multi-scale network waveform filter in the space-time adaptive processing module to obtain an interference suppression processing result; determining a space-time two-dimensional weight vector and a minimum variance distortion-free response optimization equation based on the interference suppression processing result, and performing a directional iterative search based on the space-time two-dimensional weight vector and the minimum variance distortion-free response optimization equation to obtain a search signal.

[0087] After the dimensionality reduction processing by the A / D module, the data is transmitted to the STAP (Space-Time Adaptive Processing) module to output the search signal. In order to suppress broadband interference and reduce the amount of calculation, the STAP module uses MSNWF to process the interference subspace. The MSNWF structure is as follows Figure 6 As shown in the figure. i , d i and represent the weight coefficient of the i-th level Wiener filter, the expected signal and the filtering error respectively; h i Represents the i-th stage matched filter, which is the normalized vector of the cross-correlation between the previous stage desired signal and the input data, that is, is the i-th level blocking matrix, satisfying B i h i =0, for "blocking" There are many ways to choose the blocking matrix, and the best choice is B i =Ih i h i H , at this time the matched filter is unit orthogonal.

[0088] By formula derivation, it can be seen that the subspace spanned by the matched filters at each level of the multi-level nested Wiener filtering satisfies:

[0089] Φ J=span{h1 h2…h D}=span{e1 e2…e D}

[0090] Among them, h represents the column vector of the matrix, which represents the weight or coefficient of a certain feature or attribute. j ={e1e2 ... e D} represents the interference signal subspace, let A J ={h1 h2 ... h D}. QR decomposition can be used to solve the orthogonal basis vectors of the AJ null space. A J =QU, where the column orthogonal matrix Q is of MN×MN dimension and the upper triangular matrix U is of MN×D dimension. Since AJ is a column full rank matrix, let the column vector of the matrix Q be expressed as Q=[q1,q2,…,q MN ],So

[0091] Φ J =span <q1,q2,…,q D >

[0092] Since the matrix Q is an orthogonal matrix, the space spanned by its last MN-D column vectors is orthogonal to the space spanned by the first D vectors, so these MN-D orthogonal vectors can be used as the orthogonal basis vectors of AJ, and its matrix form can be expressed as

[0093] H=[q D+1 ,q D+2 ,…,q MN ]

[0094] After obtaining MN-D orthogonal basis vectors, it is necessary to obtain the space-time two-dimensional weight vector w (MN×1 dimension) in the null space of AJ, d=[d1,d2,...,d MN-D ] T , linear combination of the orthogonal basis, we can get

[0095] w=H[d1,d2,…,d MN-D ] T =Hd

[0096] If the beam is required to have the maximum gain in the direction of the desired signal, then w=a(θ0,f c ), that is, Hd=a(θ0,f c ), θ0 is the direction of the satellite signal, f c is the carrier frequency of the satellite signal, a is a function, according to the input vector θ0 and f c To calculate a value w. The coefficient matrix H is an overdetermined equation with full column rank, so the vector d can be obtained using the least squares method (LS)

[0097] d=(H H H) -1 H H a(θ0,f c )

[0098] Substitute into the formula w=H[d1,d2,…,d MN-D ] T =Hd, we can get the final weight vector

[0099] w=H(H H H) -1 H H a(θ0,f c )

[0100] After MSNWF processes the data, it obtains the final weight vector mentioned above, and then completes the satellite signal search through space-time adaptive processing.

[0101] exist Figure 2 In {w nm}(m=1,2,··,M,n=1,2,…,N) are the space-time two-dimensional weight coefficients. Let the time interval of each beat be T, which is usually required to be no greater than 1 / B, and B is the signal bandwidth; the total delay length of each array element signal is (N-1)T, which is required to be greater than the maximum multipath delay. Let the received signals of M array elements be expressed as x1(n),…,x M (n), then the input signals of each FIR tap after array element m are:

[0102] x m1 (n) = x m (n),x m2 (n) = x m (n-1),…,x mN (n) = x m (n-N+1)

[0103] Let X represent the input signal matrix:

[0104] X=[x 11 ,x 12 ,…,x 1N ,x 21 ,x 22 ,…,x 2N ,…,x M1 ,x M2 ,…,x MN ] T

[0105] Use MN×1 dimensional vector w to represent the processor weight vector, then

[0106] w=[w 11 ,w 12,…,w 1N ,w 21 ,w 22 ,…,w 2N ,…,w M1 ,w M2 ,…,w MN ] T

[0107] The covariance matrix of the data received by each array element can be expressed as R=E[XX H ](MN×MN dimensions), by the linearly constrained minimum variance criterion, the processor can be described as the following optimization problem

[0108] P out =w H R

[0109] w н S=1

[0110] If ws and wt represent the spatial normalized frequency and the temporal normalized frequency respectively, represents the Kronach product, then the space-time two-dimensional steering vector S can be written as

[0111]

[0112] Where, the space steering vector Ss and the time steering vector St are expressed as:

[0113]

[0114] For a broadband multilinear constrained minimum variance processor, K constraints are set. K is the same as the number of channel delay units, N. The first constraint is that when a unit plane wave with an angular frequency of w1 is incident on the array at θ1, the array output (i.e., the array response) is b1. The first constraint can be written as:

[0115]

[0116] In the formula The kth constraint is that when a unit plane wave with an angular frequency of wk is incident on the array at θk, the output of the array (i.e., the response of the array) is bk. The kth constraint equation can be obtained as:

[0117]

[0118] Therefore, the minimum variance LCMV optimization equation with K linear constraints is:

[0119] E{|y(n)| 2}=w H R

[0120] C H w=b

[0121] Where E is the expected value, y(n) is the amplitude of the signal, n is the code phase, w is the code rate, C is the constraint matrix, b is the response vector, and H is the transposed matrix. k ], output response vector b=[b1,b2,…,b K ] T Using the Lagrange multiplier method, the satellite signal frequency can be

[0122] y (n) =R -1 C(C H R -1 C) -1 b

[0123] Where C is the constraint matrix, b is the response vector, y (n) is the signal frequency, and R is the covariance matrix of the data received by each array element.

[0124] The entire satellite search process: within the range of θ∈[θ1,θ2], the search step is Δθ to implement the following steps:

[0125] Iterative initialization:

[0126]

[0127] X0(k)=X(k)-h0d0(k)

[0128] Forward iterative process:

[0129] for i=1,2,…,D,D+1

[0130]

[0131]

[0132] X i (k) = X i-1 (k)-h i d i (k)

[0133] In the above, δ represents the variational vector, i is a natural number such as 1, 2, 3, and E represents the unit vector. Satellite signal search process:

[0134] A J =[h1 h2 … h D ]=QD

[0135] Q=[q1,q2,…,q MN ]

[0136] H=[qD+1 ,q D+2 ,...,q MN ]

[0137] H p =H(H H H) -1 H H

[0138] for? θ=θ1,Δθ,2Δθ,…,θ2

[0139] y (n) =H p a(θ,f c )

[0140] Through the above steps, the BOC code correlation branch can be used to optimize the search of 128 frequencies into a single search. In the one-dimensional code phase, 100 parallel correlators are used to search 100 code phases at a time, reducing the number of searches from 128 × 8184 to 82. This reduces the number of searches and utilizes a dimensionality-reduction space-time beamforming algorithm: Before searching for signals, a QR decomposition is performed. A combined method combining a fast Householder QR decomposition algorithm and back substitution for solving triangular matrix equations is then used. When searching for satellites at different angles, the QR decomposition value from the initial decomposition can be used, requiring only O(MN) computational complexity. This reduces the algorithm's computational complexity and improves search efficiency, significantly increasing the speed of searching for satellites at different angles during satellite communications and improving the overall efficiency of the algorithm. This addresses the low search efficiency caused by the high number of searches and computational complexity of traditional satellite signal searches, providing strong technical support for the rapid and efficient development of satellite communications.

[0141] The present invention provides a satellite signal search device. Figure 7 is a structural diagram of the device, such as Figure 7 As shown, the device includes: a first processing module 70, which is used to perform correlation operation, time integration and sampling processing on the satellite signal to be processed through the binary offset carrier code correlation branch in the target array element after the target array element in the satellite antenna array receives the satellite signal to be processed, so as to obtain a first processing result and determine the signal peak information of the satellite signal to be processed, wherein the target array element is any array element in the satellite antenna array; a second processing module 72, which is used to perform dimensionality reduction processing on the first processing result according to the signal peak information through the analog-to-digital converter in the target array element, so as to obtain a second processing result; a third processing module 74, which is used to reduce the dimension of the second processing result corresponding to each array element through the space-time adaptive processing module in the satellite antenna array and suppress broadband interference in the second processing result, so as to obtain a search signal, wherein the search signal is used to determine the communication satellite that sends the satellite signal to be processed.

[0142] In some embodiments of the present application, a correlation operation is performed on the signal to be processed by a binary offset carrier code correlation branch in the target array element. Before time integration and sampling processing, the method further includes: performing time domain filtering processing on the satellite signal to be processed by an N-order finite impulse response filter set in the target array element, and using the satellite signal to be processed after the time domain filtering processing as the input signal of the binary offset carrier code correlation branch, where N is an arbitrary positive integer.

[0143] In some embodiments of the present application, processing a signal to be processed by a binary offset carrier code correlation branch in a target array element includes: determining a digital intermediate frequency signal in the satellite signal to be processed, wherein the frequency of the digital intermediate frequency signal is within a preset frequency value range; generating a local carrier signal and a local pseudo code by a carrier controlled oscillator in the binary offset carrier code correlation branch, and performing sub-wave modulation on the local pseudo code to obtain a local binary offset carrier code, wherein the local carrier signal includes two signal components, namely, in-phase and orthogonal signals; performing a correlation operation on the digital intermediate frequency signal with the local binary offset carrier code and the local pseudo code to obtain a correlation operation result, and performing time integration and sampling processing on the correlation operation result to obtain a first processing result.

[0144] In some embodiments of the present application, a digital intermediate frequency signal is correlated with a local binary offset carrier code and a local pseudo code to obtain a correlation operation result, and the correlation operation result is time-integrated and sampled to obtain a first processing result, including: correlating the digital intermediate frequency signal with the local binary offset carrier code to obtain a first correlation operation result; correlating the digital intermediate frequency signal with the local pseudo code to obtain a second correlation operation result; performing integral sampling processing on the first correlation operation result to obtain a first sampling result, and performing integral sampling processing on the second correlation operation result to obtain a second sampling result, wherein the first sampling result and the second sampling result are the first processing results.

[0145] In some embodiments of the present application, after performing integral sampling processing on the first correlation operation result to obtain a first sampling result, and performing integral sampling processing on the second correlation operation result to obtain a second sampling result, the method further includes: performing a modulo square operation on the first sampling result to obtain a first signal strength value, wherein the first signal strength value is used to reflect the degree of matching between the binary offset carrier code in the digital intermediate frequency signal and the local binary offset carrier code; performing a modulo square operation on the second sampling result to obtain a second signal strength value, wherein the second signal strength value is used to reflect the degree of matching between the binary offset carrier code in the digital intermediate frequency signal and the local pseudo code; determining the difference between the first signal strength value and the second signal strength value, and determining the signal peak information based on the difference, wherein the signal peak information includes the frequency value range of the local carrier signal when the difference value is the peak value, and the phase value range of the local pseudo code.

[0146] In some embodiments of the present application, performing dimensionality reduction processing on the first processing result based on signal peak information by an analog-to-digital converter in a target array element to obtain a second processing result includes: performing multiple orthogonal projection decompositions on the first processing result to obtain the second processing result, wherein the second processing result includes a covariance matrix, and the dimension of the covariance matrix is ​​lower than the dimension of the first processing result.

[0147] In some embodiments of the present application, the dimension of the second processing result corresponding to each array element is reduced by a space-time adaptive processing module in a satellite antenna array, and broadband interference in the second processing result is suppressed to obtain a search signal, including: performing dimensionality reduction processing on the second processing result by a dimensionality reduction multi-scale network waveform unit in the space-time adaptive processing module to obtain a dimensionality reduction processing result; performing interference suppression processing on the dimensionality reduction processing result by a multi-scale network waveform filter in the space-time adaptive processing module to obtain an interference suppression processing result; determining a space-time two-dimensional weight vector and a minimum variance distortion-free response optimization equation based on the interference suppression processing result, and performing a directional iterative search based on the space-time two-dimensional weight vector and the minimum variance distortion-free response optimization equation to obtain a search signal.

[0148] It should be noted that the various modules in the above-mentioned satellite signal search device can be program modules (for example, a set of program instructions that implement a certain specific function) or hardware modules. For the latter, it can be expressed in the following forms, but is not limited to this: the expression form of each of the above-mentioned modules is a processor, or the functions of each of the above-mentioned modules are implemented by a processor.

[0149] An embodiment of the present application provides a non-volatile storage medium, in which a program is stored, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute the following satellite signal search method: after a target array element in a satellite antenna array receives a satellite signal to be processed, a correlation operation, time integration and sampling processing are performed on the satellite signal to be processed through a binary offset carrier code correlation branch in the target array element to obtain a first processing result and determine the signal peak information of the satellite signal to be processed, wherein the target array element is any array element in the satellite antenna array; the first processing result is subjected to dimensionality reduction processing by an analog-to-digital converter in the target array element according to the signal peak information to obtain a second processing result; the dimension of the second processing result corresponding to each array element is reduced by a space-time adaptive processing module in the satellite antenna array and broadband interference in the second processing result is suppressed to obtain a search signal, wherein the search signal is used to determine the communication satellite that sends the satellite signal to be processed.

[0150] An embodiment of the present application provides an electronic device, comprising: a memory and a processor, the processor being configured to run a program stored in the memory, wherein the following satellite signal search method is executed when the program is run: after a target array element in a satellite antenna array receives a satellite signal to be processed, a correlation operation, time integration, and sampling processing are performed on the satellite signal to be processed through a binary offset carrier code correlation branch in the target array element to obtain a first processing result and determine signal peak information of the satellite signal to be processed, wherein the target array element is any array element in the satellite antenna array; dimensionality reduction processing is performed on the first processing result based on the signal peak information through an analog-to-digital converter in the target array element to obtain a second processing result; and the dimension of the second processing result corresponding to each array element is reduced through a space-time adaptive processing module in the satellite antenna array and broadband interference in the second processing result is suppressed to obtain a search signal, wherein the search signal is used to determine the communication satellite that sends the satellite signal to be processed.

[0151] An embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the following satellite signal search method: after a target array element in a satellite antenna array receives a satellite signal to be processed, a binary offset carrier code correlation branch in the target array element is used to perform correlation operations, time integration, and sampling processing on the satellite signal to be processed to obtain a first processing result and determine signal peak information of the satellite signal to be processed, wherein the target array element is any array element in the satellite antenna array; an analog-to-digital converter in the target array element is used to perform dimensionality reduction processing on the first processing result based on the signal peak information to obtain a second processing result; and a space-time adaptive processing module in the satellite antenna array is used to reduce the dimension of the second processing result corresponding to each array element and suppress broadband interference in the second processing result to obtain a search signal, wherein the search signal is used to determine the communication satellite that sends the satellite signal to be processed.

[0152] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0153] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0154] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected to achieve the purpose of the present embodiment according to actual needs.

[0155] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0156] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the relevant technology, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0157] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A satellite signal search method, characterized in that: include: After a target array element in a satellite antenna array receives a satellite signal to be processed, a correlation operation, time integration, and sampling processing are performed on the satellite signal to be processed through a binary offset carrier code correlation branch in the target array element to obtain a first processing result and determine signal peak information of the satellite signal to be processed, wherein the target array element is any array element in the satellite antenna array; The satellite signal to be processed is correlated with the binary offset carrier code correlation branch in the target array element, and the time integration and sampling processing include: determining the digital intermediate frequency signal in the satellite signal to be processed, wherein the frequency of the digital intermediate frequency signal is within a preset frequency value range; generating a local carrier signal and a local pseudo code through a carrier control oscillator in the binary offset carrier code correlation branch, and performing sub-wave modulation on the local pseudo code to obtain a local binary offset carrier code, wherein the local carrier signal includes two signal components of in-phase and orthogonal phase; and combining the digital intermediate frequency signal with the local binary offset carrier code and the local pseudo code. performing a correlation operation to obtain a correlation operation result, and performing time integration and sampling processing on the correlation operation result to obtain the first processing result, including: performing a correlation operation on the digital intermediate frequency signal and the local binary offset carrier code to obtain a first correlation operation result; performing a correlation operation on the digital intermediate frequency signal and the local pseudo code to obtain a second correlation operation result; performing integral sampling processing on the first correlation operation result to obtain a first sampling result, and performing integral sampling processing on the second correlation operation result to obtain a second sampling result, wherein the first sampling result and the second sampling result are the first processing result; Performing dimensionality reduction processing on the first processing result according to the signal peak information by an analog-to-digital converter in the target array element to obtain a second processing result, including: performing multiple orthogonal projection decompositions on the first processing result to obtain the second processing result, wherein the second processing result includes a covariance matrix, and the dimension of the covariance matrix is ​​lower than the dimension of the first processing result; The space-time adaptive processing module in the satellite antenna array reduces the dimension of the second processing result corresponding to each array element and suppresses broadband interference in the second processing result to obtain a search signal, wherein the search signal is used to determine the communication satellite that sends the satellite signal to be processed.

2. The satellite signal search method according to claim 1, wherein: Performing a correlation operation on the satellite signal to be processed through a binary offset carrier code correlation branch in the target array element, before time integration and sampling processing, the method further includes: The satellite signal to be processed is subjected to time domain filtering processing by an N-order finite impulse response filter set in the target array element, and the satellite signal to be processed after the time domain filtering processing is used as the input signal of the binary offset carrier code correlation branch, where N is an arbitrary positive integer.

3. The satellite signal search method according to claim 1, wherein: After performing integral sampling processing on the first correlation operation result to obtain a first sampling result, and performing integral sampling processing on the second correlation operation result to obtain a second sampling result, the method further includes: Performing a modulo square operation on the first sampling result to obtain a first signal strength value, wherein the first signal strength value is used to reflect the degree of matching between the binary offset carrier code in the digital intermediate frequency signal and the local binary offset carrier code; Performing a modulo square operation on the second sampling result to obtain a second signal strength value, wherein the second signal strength value is used to reflect the degree of matching between the binary offset carrier code in the digital intermediate frequency signal and the local pseudo code; Determine the difference between the first signal strength value and the second signal strength value, and determine the signal peak information based on the difference, wherein the signal peak information includes the frequency value range of the local carrier signal when the difference is a peak value, and the phase value range of the local pseudocode.

4. The satellite signal search method according to claim 1, wherein: Reducing the dimension of the second processing result corresponding to each of the array elements and suppressing broadband interference in the second processing result by a space-time adaptive processing module in the satellite antenna array to obtain a search signal includes: Performing dimensionality reduction processing on the second processing result by a dimensionality reduction multi-scale network waveform unit in the space-time adaptive processing module to obtain a dimensionality reduction processing result; Performing interference suppression processing on the dimensionality reduction processing result by using a multi-scale network waveform filter in the space-time adaptive processing module to obtain an interference suppression processing result; A space-time two-dimensional weight vector and a minimum variance distortion-free response optimization equation are determined according to the interference suppression processing result, and a directional iterative search is performed according to the space-time two-dimensional weight vector and the minimum variance distortion-free response optimization equation to obtain the search signal.

5. A satellite signal search device, characterized in that: Suitable for executing the satellite signal search method according to any one of claims 1 to 4, comprising: a first processing module configured to, after a target array element in a satellite antenna array receives a satellite signal to be processed, perform a correlation operation, time integration, and sampling processing on the satellite signal to be processed through a binary offset carrier code correlation branch in the target array element, to obtain a first processing result and determine signal peak information of the satellite signal to be processed, wherein the target array element is any array element in the satellite antenna array; The first processing module is further configured to perform correlation operations on the satellite signal to be processed through a binary offset carrier code correlation branch in the target array element. The time integration and sampling processing includes: determining a digital intermediate frequency signal in the satellite signal to be processed, wherein the frequency of the digital intermediate frequency signal is within a preset frequency value range; generating a local carrier signal and a local pseudo code through a carrier controlled oscillator in the binary offset carrier code correlation branch, and performing secondary wave modulation on the local pseudo code to obtain a local binary offset carrier code, wherein the local carrier signal includes two in-phase and orthogonal signal components; and combining the digital intermediate frequency signal with the local binary offset carrier code and the local pseudo code. The local pseudo code is correlated to obtain a correlation operation result, and the correlation operation result is time-integrated and sampled to obtain the first processing result, including: correlating the digital intermediate frequency signal with the local binary offset carrier code to obtain a first correlation operation result; correlating the digital intermediate frequency signal with the local pseudo code to obtain a second correlation operation result; performing integral sampling processing on the first correlation operation result to obtain a first sampling result, and performing integral sampling processing on the second correlation operation result to obtain a second sampling result, wherein the first sampling result and the second sampling result are the first processing result; A second processing module is configured to perform dimensionality reduction processing on the first processing result based on the signal peak information by an analog-to-digital converter in the target array element to obtain a second processing result, including: performing multiple orthogonal projection decompositions on the first processing result to obtain the second processing result, wherein the second processing result includes a covariance matrix, and the dimension of the covariance matrix is ​​lower than the dimension of the first processing result; The third processing module is used to reduce the dimension of the second processing result corresponding to each array element and suppress broadband interference in the second processing result through the space-time adaptive processing module in the satellite antenna array, so as to obtain a search signal, wherein the search signal is used to determine the communication satellite that sends the satellite signal to be processed.

6. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a program, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute the satellite signal search method according to any one of claims 1 to 4.

7. An electronic device, characterized in that: include: A memory and a processor, wherein the processor is configured to run a program stored in the memory, wherein the satellite signal search method according to any one of claims 1 to 4 is executed when the program is run.

8. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the satellite signal search method according to any one of claims 1 to 4 are implemented.

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