A method, device, electronic device and storage medium for real-time capture of spread spectrum signals

Abstract

The present invention relates to the field of satellite communications and provides a method, device, electronic device and storage medium for real-time capture of spread spectrum signals. The real-time capture method for spread spectrum signals includes: traversing Doppler frequency deviation gears to capture spread spectrum signals and determine the initial code phase and initial frequency value; performing window sliding frequency measurement in the adjacent code chip range of the initial code phase to determine the residual frequency deviation estimate; determining a rough frequency estimate based on the residual frequency deviation estimate and the initial frequency value; and performing spread spectrum signal capture again based on the rough frequency estimate to obtain the code phase value output by the spread spectrum capture. The present application reduces the search of three dimensions of code phase, frequency and code Doppler to two dimensions of phase and frequency, which is closer to the engineering application of satellite communications, can solve the signal capture problem under large code Doppler conditions, and can significantly reduce the storage capacity in existing capture solutions.

Description

Technical Field

[0001] The present invention belongs to the field of satellite communications and wireless communications, and in particular relates to a method, device, electronic equipment and storage medium for real-time capture of spread spectrum signals. Background Art

[0002] Spread-spectrum signal capture is the first step in receiving and processing spread-spectrum signals and is an essential component of spread-spectrum signal processing. Its primary task is to perform coarse synchronization of code phase, time slot, and frequency on the baseband IQ data processed by the digital front-end, facilitating subsequent tracking while reducing tracking time. Current spread-spectrum signal capture solutions employ compressed sensing and large-scale FFT (Fast Fourier Transform) / IFFT (Inverse Fast Fourier Transform) search methods to address search speed issues. However, compressed sensing and large-scale FFT / IFFT often involve complex mathematical operations, resulting in excessive computational complexity and increased consumption of computing and storage resources. Summary of the Invention

[0003] The embodiments of the present application provide a method, device, electronic device, and storage medium for real-time capture of spread spectrum signals to solve the problem of high computational complexity during the spread spectrum signal capture process.

[0004] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by practice of the present application.

[0005] According to the first aspect of the embodiment of the present application, a method for real-time capture of spread spectrum signals is provided, including: traversing the Doppler frequency deviation gear to capture the spread spectrum signal, and determining the initial code phase and initial frequency value; performing window sliding frequency measurement in the adjacent code chip range of the initial code phase to determine the residual frequency deviation estimate; determining a rough frequency estimate based on the residual frequency deviation estimate and the initial frequency value; and performing spread spectrum signal capture again based on the rough frequency estimate to obtain the code phase value output by the spread spectrum capture. The present application reduces the search of three dimensions of code phase, frequency, and code Doppler to two dimensions of phase and frequency, which is closer to the engineering application of satellite communications, can solve the signal capture problem under large code Doppler conditions, and can significantly reduce the storage capacity in existing capture solutions.

[0006] In one embodiment of the present application, the Doppler frequency deviation gear is divided according to the maximum Doppler frequency deviation of the carrier and the frequency bin interval; wherein, the frequency bin interval is determined by the frequency offset corresponding to the signal peak value dropping by a preset decibel during the signal capture simulation process.

[0007] In one embodiment of the present application, traversing the Doppler frequency deviation gears to capture the spread spectrum signal and determine the initial code phase and initial frequency value specifically includes: determining the number of time slots required for capture; at each Doppler gear, performing offset accumulation on the data within the determined number of time slots, and selecting the maximum value in the offset accumulation result as the correlation value of the corresponding gear; using the gear value corresponding to the largest correlation value in all Doppler gears as the initial frequency value, and determining the initial code phase value according to the position of the largest correlation value.

[0008] In one embodiment of the present application, the number of time slots required for capture is determined based on the number of time slots required to achieve a preset capture success rate under simulation conditions of a minimum signal-to-noise ratio and no frequency offset.

[0009] In one embodiment of the present application, the data within a determined number of time slots are subjected to staggered accumulation, and the maximum value in the staggered accumulation result is selected as the correlation value of the corresponding gear, specifically including: using the selected Doppler frequency deviation gear value to perform mixing, segmented accumulation and correlation operations on the sampled data to obtain numerical sequence data; staggering the numerical sequence data of each time slot based on the selected Doppler frequency deviation gear value, and accumulating the numerical sequence data of the selected time slot after staggering to obtain a staggered accumulation value sequence; using the maximum value in the staggered accumulation value sequence as the correlation value of the Doppler frequency deviation gear, and recording its serial number in the staggered accumulation value sequence.

[0010] In one embodiment of the present application, the window sliding frequency measurement is performed in the adjacent code chip range of the initial code phase to determine the residual frequency offset estimate, which specifically includes: selecting the staggered data of the required time slot corresponding to the initial code phase and the code phase sampling points in the adjacent code chip range based on the initial frequency value stagger; for the staggered data corresponding to each code phase, performing segmented accumulation within the time slot, taking the absolute value after FFT processing, and accumulation between time slots to obtain the maximum value of the staggered accumulation results corresponding to each code phase; and determining the residual frequency offset estimate according to the position of the maximum value among the maximum values ​​of each staggered accumulation result.

[0011] In one embodiment of the present application, the spread spectrum signal is captured again based on the rough frequency estimate to obtain the code phase value output by the spread spectrum capture, including: using the rough frequency estimate as the frequency gear, staggering the data of each time slot, and performing staggered accumulation, and taking the position of the maximum value in the staggered accumulation result as the code phase value of the spread spectrum capture.

[0012] In one embodiment of the present application, the misalignment accumulation specifically includes: calculating the misalignment value of each time slot; the misalignment value is determined by the number of code bits in the time slot, the time slot number, the number of single code bit sampling points, the relative movement speed of the satellite and the receiving end corresponding to the frequency gear, and the speed of light; and the data of each time slot is misaligned and selected according to the misalignment value.

[0013] According to a second aspect of an embodiment of the present application, a real-time capture device for a spread spectrum signal is provided, comprising: a primary capture module for dividing Doppler frequency deviation gears, traversing the Doppler frequency deviation gears to capture a spread spectrum signal, and determining an initial code phase and an initial frequency value; a residual frequency deviation estimation module for performing window sliding frequency measurement in a range of adjacent code chips of the initial code phase to determine a residual frequency deviation estimate; a frequency estimate update module for determining a coarse frequency estimate based on the residual frequency deviation estimate and the initial frequency value; and a secondary capture module for performing spread spectrum signal capture again based on the coarse frequency estimate to obtain a code phase value output by the spread spectrum capture.

[0014] According to a third aspect of an embodiment of the present application, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executes the real-time capture method of spread spectrum signals as described in the first aspect.

[0015] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer program instructions are stored. When the program instructions are executed by a processor, they are used to implement the process corresponding to the real-time capture method of spread spectrum signals described in the first aspect.

[0016] The aforementioned main solution of this application and its further options can be freely combined to form multiple solutions, all of which can be adopted and protected by this application. After understanding the solution of this application, those skilled in the art will understand that there are many combinations based on existing technology and common knowledge, all of which are technical solutions to be protected by this application, and these are not exhaustive here. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0018] Figure 1 This is a schematic diagram of the spread spectrum receiver principle.

[0019] Figure 2 This is a flow chart of the real-time capture method of spread spectrum signals according to an embodiment of the present application.

[0020] Figure 3 Schematic diagram of a method for real-time capture of spread spectrum signals according to an embodiment of the present application.

[0021] Figure 4 This is a schematic diagram of the baseband IQ data signal structure.

[0022] Figure 5This is a schematic diagram of a gear search simulation according to an embodiment of the present application.

[0023] Figure 6 This is a window search frequency measurement simulation diagram of an embodiment of the present application.

[0024] Figure 7 It is a schematic diagram of an electronic device according to an embodiment of the present application.

[0025] Figure 8 It is a structural diagram of a computer system suitable for implementing the electronic device of the embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to make the objectives, technical solutions and advantages of the present invention more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments.

[0027] All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in this application without creative effort are within the scope of protection of this application. The embodiments and features in the embodiments in this application may be combined with each other in any manner unless there is a conflict. Furthermore, although a logical order is shown in the flowcharts, in some cases, the steps shown or described may be performed in an order different from that shown.

[0028] The term "comprising" and any variations thereof in the specification and claims of this application and the accompanying drawings are intended to cover non-exclusive protection. For example, a process, method, system, product, or apparatus comprising a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to the process, method, product, or apparatus.

[0029] In this application, "multiple" can mean at least two, for example, two, three or more, and this embodiment of the application does not limit this. In the technical solution of this application, the collection, dissemination, and use of data are in compliance with the requirements of relevant national laws and regulations.

[0030] like Figure 1 As shown in the figure, spread spectrum signal capture in a digital receiver is a collection of fully digital functions, after the DFE (Decision Feedback Equalizer) and before spread spectrum tracking. Current spread spectrum signal capture solutions have the following main problems:

[0031] (1) High computational complexity. Most existing solutions require compressed sensing calculations. Compressed sensing methods require sparse representation and reconstruction of sampled data. Sparse representation is usually achieved through dictionary-based methods, such as sparse representation dictionaries and wavelet transforms, which require complex matrix operations. Commonly used methods for reconstructing and restoring the original signal are usually optimization algorithms, such as least squares and iterative thresholds, which involve matrix inversion, high-order matrix multiplication operations, and multiple iterations. Alternatively, existing solutions often require multiple large-scale FFTs, large-scale IFFTs, and large-scale FFT / IFFTs. In other words, existing technical calculations involve relatively complex mathematical operations.

[0032] (2) The computational storage overhead is large. The existing solution requires data to be collected and stored. For situations with low signal-to-noise ratios, the amount of data that needs to be stored increases exponentially. For complex processing processes, temporary data generated by the computational process also needs to be stored. Before all code phases are searched and the code phase capture results are obtained, the collected data is still stored in the storage unit and cannot be released, resulting in inefficient reuse of storage resources and high storage overhead. The amount of storage required for subsequent tracking is small, and the high storage space allocated for capture alone is low because the capture function is only enabled in a few scenarios such as initial access or tracking failure. Therefore, the large storage space leads to low storage resource utilization.

[0033] Based on this, the embodiment of the present application proposes a real-time capture method for spread spectrum signals, which greatly reduces the computational complexity and storage capacity, and achieves excellent capture performance by reducing the search in three dimensions of code phase, frequency, and code Doppler to two dimensions of phase and frequency. It only uses low-complexity calculation methods such as correlation and accumulation operations, and a storage scheme based on the offset accumulation results of the gear position to cover the original data storage unit. Please refer to Figure 2 The specific plan is as follows:

[0034] S100: Traverse the Doppler frequency deviation gears to capture the spread spectrum signal and determine the initial code phase and initial frequency values.

[0035] In this embodiment, by binning Doppler frequency deviation, the original three-dimensional search of code phase, frequency, and code Doppler is reduced to a two-dimensional search, achieving excellent acquisition performance. Therefore, when acquiring a spread-spectrum signal, the Doppler frequency deviation is first divided into bins based on the carrier's maximum Doppler frequency deviation and the frequency bin interval. The frequency bin interval is determined by the frequency offset corresponding to a preset decibel drop in the signal peak during the signal acquisition simulation.

[0036] If the real-time received data stream signal is :

[0037]

[0038] in, is the signal amplitude; is the code element of signal modulation; is a pseudo-random code; is the pseudo code offset phase, is the Doppler frequency deviation of the carrier, ∆T is the sampling time interval, is Gaussian white noise.

[0039] Assume that the maximum Doppler frequency deviation of the carrier is , the minimum signal-to-noise ratio is , the chip rate after spreading is , baseband The data sampling rate is , the number of chips in a time slot is , the length of the primary synchronization code of a time slot is The capture success rate is ;Receive RF frequency of spread spectrum signal At this time, according to the minimum signal-to-noise ratio When the simulation only considers the frequency deviation change factor, the segmented accumulation method is used to determine the frequency offset corresponding to the preset decibel drop compared to the peak value. , and then we can get the number of Doppler frequency deviation gears .

[0040] After determining the Doppler frequency offset position, it is also necessary to determine the number of time slots required for signal capture. , in order to determine the required data length for calculation. In this embodiment, according to the minimum signal-to-noise ratio , when simulating no frequency deviation, the segmented accumulation method is used to achieve the capture success rate The number of time slots required , which ultimately determines the number of time slots required for real-time capture .

[0041] It should be noted that, in this embodiment, the data in the time slot is processed by a segmented accumulation method to save storage space, specifically as follows: Assume that the M sample data in a time slot are , the segmented accumulation processing of M data is as follows:

[0042]

[0043]

[0044] in, is the spread spectrum code sequence, which is determined as a known condition when the spread spectrum communication system is designed.

[0045] The final segmented accumulation result , where the absolute value is calculated using an approximate method, namely:

[0046] .

[0047] After determining the Doppler frequency deviation position and number of time slots After that, you can perform a two-dimensional search. Figure 3 In this embodiment, a coarse code Doppler search is first performed based on the P determined Doppler frequency offset positions, followed by a coarse acquisition confirmation. Specifically, at each Doppler position, the data within a determined number of time slots is accumulated, and the maximum value of the accumulated offsets is selected as the correlation value for the corresponding position. The position value corresponding to the maximum correlation value across all Doppler positions is used as the initial frequency value, and the initial code phase value is determined based on the position of the maximum correlation value.

[0048] During the search process, inter-time slot data is processed using a staggered accumulation method, which, in conjunction with the segmented accumulation method for data within a time slot, can significantly reduce storage requirements. Specifically, in this embodiment, the staggered accumulation process includes: performing frequency mixing, segmented accumulation, and correlation operations on the sampled data using the selected Doppler frequency offset level to obtain numerical sequence data; staggering the numerical sequence data of each time slot based on the selected Doppler frequency offset level, and accumulating the staggered numerical sequence data of the selected time slots to obtain a staggered accumulated value sequence; and determining the maximum value in the staggered accumulated value sequence as the correlation value for that Doppler frequency offset level, and recording its sequence number in the staggered accumulated value sequence. This sequence number can be used to determine the initial code phase value.

[0049] This application calculates the number of staggered sampling points between time slots according to the code Doppler gear situation, realizes the staggered accumulation between time slots, and greatly reduces the storage capacity, reducing the storage capacity of multiple time slots to the cumulative value storage capacity of one time slot. In one embodiment, during the staggered accumulation process, the staggered value used is for:

[0050]

[0051] in, Indicates the number of chips in a time slot, Indicates the number of time slots corresponding to real-time capture, Indicates the time slot number, Indicates the number of sampling points of a chip, Indicates the relative speed between the user terminal and the satellite corresponding to the frequency gear. Based on the offset value corresponding to each time slot, the offset selection data is completed, and the offset selection data is subsequently accumulated to complete the offset accumulation process.

[0052] Assume that a chip samples I data points. Taking no Doppler shift as an example, there is no Doppler at this time. The accumulated misalignment is reflected in the following three rows of vectors, each row +1 point corresponds to addition. When implemented in hardware, only the cumulative result needs to be stored. When a new packet of data arrives, the three steps of reading the cumulative result, adding it to the new data, and storing the cumulative result are performed:

[0053]

[0054]

[0055] …

[0056]

[0057] After adding the corresponding The +1 numbers are as follows:

[0058]

[0059]

[0060] …

[0061] .

[0062] Due to the large signal dynamics, the code phase value after completing the multi-gear search may drift significantly due to code Doppler. To reduce the complexity of subsequent frequency measurement searches, please continue to refer to Figure 3 In this embodiment, a search is performed again according to the determined initial frequency value as the only gear value (i.e., coarse capture confirmation), the code phase value is re-determined, and the code phase value is used as the final initial code phase.

[0063] Through the capture method of the embodiment of the present application, in the code phase estimation process of each gear, the code phase estimation result can output the captured code phase within a few clock cycles after the last data input participating in the capture operation, and the capture has good real-time performance; the data participating in the staggered accumulation operation is obtained from the baseband IQ data through parallel correlation. The parallel correlation operation only involves addition and subtraction operations and is implemented by engineering.

[0064] S200: Perform window sliding frequency measurement in a range of adjacent code chips of the initial code phase to determine a residual frequency offset estimate.

[0065] There may be residual frequency offset estimates that were not obtained during the first capture. Please continue to refer to Figure 3In this embodiment, a window sliding frequency measurement method is used to obtain a residual frequency offset estimate, which is used to subsequently determine a rough frequency estimate. Specifically, first, based on the initial frequency value offset, the initial code phase and the offset data of the required time slot corresponding to the code phase sampling point within the adjacent code chip range are selected; then, for the offset data corresponding to each code phase, segmented accumulation within the time slot, absolute value after FFT processing, and accumulation between time slots are performed to obtain the maximum value of the offset accumulation results corresponding to each code phase; finally, the residual frequency offset estimate is determined based on the position of the maximum value in the maximum value of each offset accumulation result. The segmented accumulation and offset accumulation principles used in the window sliding frequency measurement process are similar to those in S100 and will not be elaborated here.

[0066] S300: Determine a rough frequency estimate according to the residual frequency offset estimate and the initial frequency value.

[0067] In this step, the residual frequency offset estimate is superimposed on the initial frequency value to obtain the frequency output estimate, thereby completing the initial capture.

[0068] S400 , performing spread spectrum signal capture again according to the rough frequency estimation value to obtain a code phase value output by the spread spectrum capture.

[0069] Please continue to refer to Figure 3 Finally, using the rough frequency estimate as the frequency step, the spread spectrum signal is captured again (i.e., the P+1th capture) to obtain the code phase value output by the spread spectrum capture. The spread spectrum signal capture process in this step is similar to the capture process in S100. Specifically, the data within a specified number of time slots is accumulated by shifting, and the position of the maximum value in the shifted accumulation result is selected to determine the code phase value for the spread spectrum capture.

[0070] This application addresses the signal capture problem of satellite communication spread spectrum systems. Under the conditions of many unfavorable factors such as large frequency Doppler dynamics, large code Doppler variation range, and low signal-to-noise ratio, an optimization algorithm is designed through a detailed analysis of the inertial variation law of code Doppler and initial capture indicators. Only low-complexity algorithm calculation methods such as correlation and cumulative calculations, and a storage scheme of overwriting the original data storage unit based on the staggered accumulation results of the gear position are used, which greatly reduces the computational complexity and storage capacity, and achieves excellent capture performance.

[0071] Compared with the existing spread spectrum capture technology, the technical solution of this application is closer to the engineering application of satellite communications, can solve the signal capture problem under large code Doppler conditions, can greatly reduce the storage capacity of existing capture solutions, and the calculation method only involves mixing and correlation operations, which are implemented by engineering. This application reduces the search of three dimensions of code phase, frequency, and code Doppler to two dimensions of phase and frequency; this solution greatly compresses the overall storage resource consumption, and the main operations are correlation, mixing, and accumulation, which can be well designed into a hardware circuit. Due to the simple operation method, the gear search time can be greatly reduced in parallel, which is more adaptable and more applicable in actual engineering.

[0072] In order to better understand the spread spectrum signal capture method proposed in this application, the following is a specific description of the scenario where the chip rate is 5Mcps, the sampling rate of the baseband IQ data is 10MHz, one time slot has 6000 chips, the main synchronization code length in one time slot is 500, the minimum signal-to-noise ratio required for capture is -23dB, the maximum Doppler is 40kHz, the signal RF frequency is 1.5GHz, and the capture success rate is more than 90%. The signal structure is as follows Figure 4 shown.

[0073] Through simulation, it is determined that when SNR_MIN = -23dB, the number of time slots required for the segmented accumulation method to achieve a 90% capture success rate is about 15. In the absence of noise, the cumulative peak value corresponding to 15 time slots is about 7500. The peak value drops by 3dB to about 3750, and the corresponding frequency deviation is about 5kHz. Therefore, the Doppler is divided into 40 2 / 5+1=17 gears, the number of time slots is set to 30. The 6000 code phases corresponding to one time slot correspond to 6000 sampling points. 10e6 / 5e6=12000.

[0074] Taking the Doppler frequency of 40kHz as an example, the corresponding 30 offset values ​​are round(8e3 / 3e8 2 6000 (0:29)), as shown in Table 1.

[0075] Table 1

[0076]

[0077] The continuous sequence sampling data is mixed according to the frequency deviation of 40kHz to obtain the sequence , calculate the numerical sequence in real time according to the subsequent rules

[0078] For use in misalignment accumulation. Details are as follows:

[0079] First, register maintenance is required. Since the oversampling multiple is 2, two sets of registers need to be maintained. Assume that the sampling data are in chronological order: .

[0080] The first set of registers: . The second set of registers: .

[0081] After a new data comes, if the data is , then update the value of the first register to: .

[0082] If the data is , then update the value of the second group of registers to: .

[0083] The second is digital calculation. Before the new sampling point comes, it needs to be completed The cumulative processing of 500 data is:

[0084]

[0085]

[0086] Segmented cumulative results , where the absolute value is calculated using an approximate method, namely

[0087] .

[0088] The calculation method for misalignment accumulation is as follows:

[0089] Assume that the sequence after correlation is as follows according to the sampling sequence number:

[0090]

[0091] .

[0092] When there is no code Doppler, each time slot does not need to be misaligned. After the data of 30 time slots are misaligned, the sliding window sequence (that is, the obtained misalignment cumulative value sequence) The following 30 vectors are added together:

[0093]

[0094]

[0095]

[0096]

[0097] The sliding window has one more sampling point because the code Doppler may offset one sampling point in a time slot. When the offset value of each time slot caused by code Doppler is (According to the time slot number, it can be obtained by looking up Table 1), the sliding window sequence (that is, the obtained offset accumulated value sequence) The following 30 vectors are added together:

[0098]

[0099]

[0100]

[0101]

[0102] Taking into account the misalignment value The maximum value of is 9 and the sliding window length increases due to code Doppler. In order for the offset accumulation to proceed normally, the required data volume is in addition to 30 6000 2 (i.e. ) may also involve as well as , ,…, There are 18 correlation values ​​in total. Two sampling points constitute one time slot, and the search for one gear needs to span 32 time slots. However, for real-time calculation, in this embodiment, only 9 correlation values ​​need to be added before and after, for a total of 18 correlation values.

[0103] For the 40kHz frequency deviation position, after 30 time slots of misalignment accumulation, the misalignment accumulation value sequence can be obtained. There are 12001 correlation values ​​in total. Take the maximum value among the 12001 values ​​as the correlation value of the gear, and write down the serial number corresponding to the maximum value.

[0104] Calculate the correlation values ​​for each of the 17 gears , take the frequency gear value corresponding to the maximum value as the initial frequency estimate , take the serial number value corresponding to the gear as the initial code phase .

[0105] Due to the large signal dynamics, the code phase value after completing the multi-level search may drift significantly due to code Doppler. In order to reduce the complexity of the subsequent frequency measurement search, a coarse capture confirmation is required after determining the initial frequency estimate and the initial code phase. That is, a search is performed based on the initial frequency estimate as the only level value. The search process is exactly the same as the aforementioned 17-level process, except that there is only one level, and the final initial frequency estimate and initial code phase are obtained.

[0106] Perform a rough frequency estimate. For real-time sampling data, calculate the code phase offset of each time slot according to the initial frequency estimate, that is, calculate the misalignment value for:

[0107]

[0108] in, Indicates the relative motion speed between the user terminal and the satellite corresponding to the Doppler frequency offset position, which corresponds to the initial frequency estimate. Then, using the initial code phase as a reference value, extract the PSC (Primary Synchronization Code) data of 30 time slots:

[0109]

[0110] It should be noted that the PSC data here is data that has been selected through misalignment of the values.

[0111] For each segment of 500 data, divide it into 50 segments in order, with 10 data in each segment. Sum the 10 data in each segment to get 50 data. Perform 1024-point FFT on the 50 data and take the absolute value to get 1024 spectrum results:

[0112]

[0113] Add the corresponding data and get 1024 data ,in:

[0114]

[0115] from Find the maximum value in , the maximum value subscript is .

[0116] Take two sampling points in the adjacent chips of the initial code phase and perform the same operation, that is, repeatedly take the PSC data of 30 time slots for calculation to obtain the PSC under 5 sampling points. , and determine the maximum value among them, and output the subscript corresponding to the maximum value , and the residual frequency offset estimate is obtained: The final rough estimate of the frequency of the spread spectrum capture output is .

[0117] Finally, set the frequency range to , and then perform the same capture and confirmation process to estimate the code phase rough estimate , as the code phase value output by spread spectrum capture, the processing result is output within a few clock cycles after the last data involved in the operation.

[0118] To further verify the method proposed in this application, the code phase was randomly configured between [1-6000] and the frequency offset was randomly configured between -40kHz and 40kHz. The method provided in this application was simulated multiple times. The criterion for successful capture was that the code phase and the set value did not exceed half a code chip, and the criterion for successful frequency offset estimation was that the frequency error did not exceed half of the gear interval. The statistical results are as follows:

[0119] ESNO = -23dB, 30 slots, random time offset, random frequency offset, 30,000 runs, capture success rate 94.8%, frequency offset measurement success rate 94.72%, performance meets design requirements.

[0120] The results of single simulation, gear search simulation and window search frequency measurement are as follows: Figure 5 and Figure 6 As shown in the figure, under the random simulation conditions, a peak occurs in the 15th bin, corresponding to a Doppler frequency offset of 32 kHz. During window search frequency measurement, a peak occurs in the third bin within a window length of 5, and the frequency result measured by the third bin is used.

[0121] An embodiment of the present application also provides a real-time capture device for spread spectrum signals, including: a primary capture module, used to divide the Doppler frequency deviation gears, traverse the Doppler frequency deviation gears to capture spread spectrum signals, and determine the initial code phase and initial frequency value; a residual frequency deviation estimation module, used to perform window sliding frequency measurement in the adjacent code chip range of the initial code phase to determine the residual frequency deviation estimate; a frequency estimate value update module, used to determine a coarse frequency estimate based on the residual frequency deviation estimate and the initial frequency value; and a secondary capture module, used to perform spread spectrum signal capture again based on the coarse frequency estimate to obtain the code phase value output by the spread spectrum capture.

[0122] The following describes an electronic device embodiment of the present application, which can be used to perform the high-precision frequency offset estimation method in the above embodiment of the present application. For details not disclosed in the electronic device embodiment, please refer to the above embodiment of the method of the present application.

[0123] Reference Figure 7 As shown, an electronic device 500 according to an embodiment of the present application includes: a memory 501 and a processor 502, wherein the memory 501 stores a computer program that can be loaded by the processor 502 and execute the real-time spread spectrum signal capture method described in the first aspect.

[0124] Figure 8 A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown.

[0125] It should be noted that Figure 8 The computer system 600 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0126] like Figure 7 As shown, computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes, such as the methods described in the above embodiments, based on programs stored in read-only memory (ROM) 602 or programs loaded from storage 608 into random access memory (RAM) 603. RAM 603 also stores various programs and data required for system operation. CPU 601, ROM 602, and RAM 603 are interconnected via bus 604. An input / output (I / O) interface 605 is also connected to bus 604.

[0127] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, mouse, and the like; an output section 607 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and speakers; a storage section 608 including a hard disk; and a communication section 609 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable storage medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 610 as needed, so that computer programs read from the removable storage medium can be installed in the storage section 608 as needed.

[0128] In particular, according to embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for executing the methods illustrated in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication section 609 and / or installed from a removable storage medium 611. When executed by the central processing unit (CPU) 601, the computer program performs the various functions defined in the system of the present application.

[0129] It should be noted that the computer-readable medium described in the embodiments of this application may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal transmitted in baseband or as part of a carrier wave, which carries computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0130] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0131] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. In some cases, the names of these units do not constitute limitations on the units themselves.

[0132] As another aspect, the present application further provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method for real-time acquisition of spread spectrum signals described in the above embodiments.

[0133] As another aspect, the present application further provides a computer-readable medium, which may be included in the electronic device described in the above embodiments, or may exist independently and not be incorporated into the electronic device. The computer-readable medium carries one or more programs, and when executed by the electronic device, the electronic device implements the method for real-time spread spectrum signal acquisition described in the above embodiments.

[0134] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiment of the application, the features and functions of two or more modules or units described above can be concretized in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0135] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.

[0136] Those skilled in the art will understand the specific meanings of the above terms in the present invention in specific circumstances. The drawings in the embodiments are used to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0137] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

[0138] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A method for real-time acquisition of a spread spectrum signal, characterized in that: include: Traverse the Doppler frequency deviation gear to capture the spread spectrum signal and determine the initial code phase and initial frequency values; Performing window sliding frequency measurement in a range of adjacent code chips of the initial code phase to determine a residual frequency offset estimate; determining a rough frequency estimate based on the residual frequency offset estimate and the initial frequency value; performing spread spectrum signal capture again according to the coarse frequency estimation value to obtain a code phase value output by the spread spectrum capture; The performing window sliding frequency measurement in the adjacent chip range of the initial code phase to determine the residual frequency offset estimate specifically includes: selecting staggered data of a required time slot corresponding to the initial code phase and code phase sampling points in the adjacent chip range based on the initial frequency value stagger; For the staggered data corresponding to each code phase, segmented accumulation within the time slot, absolute value after FFT processing, and accumulation between time slots are performed to obtain the maximum value of the staggered accumulation results corresponding to each code phase; the residual frequency offset estimate is determined based on the position of the maximum value among the maximum values ​​of each staggered accumulation result.

2. The method for real-time acquisition of spread spectrum signals according to claim 1, wherein: The Doppler frequency deviation gear is divided according to the maximum Doppler frequency deviation of the carrier and the frequency bin interval; wherein, the frequency bin interval is determined by the frequency offset corresponding to the signal peak value dropping by a preset decibel during the signal capture simulation process.

3. The method for real-time acquisition of spread spectrum signals according to claim 1, wherein: The step of traversing the Doppler frequency deviation gears to capture the spread spectrum signal and determine the initial code phase and the initial frequency value specifically includes: Determine the number of time slots required for capture; At each Doppler level, the data within a certain number of time slots are accumulated and the maximum value of the accumulated results is selected as the correlation value of the corresponding level; The gear value corresponding to the maximum correlation value among all Doppler gears is used as the initial frequency value, and the initial code phase value is determined according to the position of the maximum correlation value.

4. The method for real-time acquisition of spread spectrum signals according to claim 3, wherein: The number of time slots required for capture is determined based on the number of time slots required to achieve a preset capture success rate under simulation conditions of a minimum signal-to-noise ratio and no frequency offset.

5. The method for real-time acquisition of spread spectrum signals according to claim 3, wherein: The step of performing staggered accumulation on the data within the determined number of time slots and selecting the maximum value of the staggered accumulation result as the relevant value of the corresponding gear specifically includes: The sampled data are mixed, segmented and accumulated, and correlated using the selected Doppler frequency offset gear value to obtain numerical sequence data; the numerical sequence data of each time slot is staggered based on the selected Doppler frequency offset gear value, and the numerical sequence data of the selected time slot after staggering are accumulated to obtain a staggered accumulated value sequence; The maximum value in the sequence of accumulated misalignment values ​​is used as the correlation value of the Doppler frequency offset gear, and its sequence number in the sequence of accumulated misalignment values ​​is recorded.

6. The method for real-time acquisition of spread spectrum signals according to claim 1, wherein: The step of again capturing the spread spectrum signal according to the rough frequency estimation value to obtain a code phase value output by the spread spectrum capture comprises: The rough frequency estimate is used as the frequency gear, the data of each time slot is staggered and accumulated, and the position of the maximum value in the staggered accumulation result is selected as the code phase value for spread spectrum capture.

7. The method for real-time acquisition of spread spectrum signals according to claim 3 or 6, wherein: Data misalignment options include: Calculating the misalignment value of each time slot; the misalignment value is determined by the number of chips in the time slot, the time slot number, the number of sampling points of a single chip, the relative motion speed of the satellite and the receiving end corresponding to the frequency gear, and the speed of light; The data of each time slot is selected by shifting according to the shift value.

8. A real-time capture device for spread spectrum signals, characterized in that: include: A primary capture module is used to divide the Doppler frequency deviation gears, traverse the Doppler frequency deviation gears to capture the spread spectrum signal, and determine the initial code phase and initial frequency values; The residual frequency offset estimation module is configured to perform window sliding frequency measurement within a range of adjacent code chips of the initial code phase to determine a residual frequency offset estimate, including: selecting staggered data of a desired time slot corresponding to the initial code phase and code phase sampling points within a range of adjacent code chips based on the initial frequency value stagger; performing segmented accumulation within a time slot, taking an absolute value after FFT processing, and accumulating the staggered data corresponding to each code phase to obtain a maximum value of the staggered accumulation results corresponding to each code phase; and determining the residual frequency offset estimate based on the position of the maximum value among the maximum values ​​of the staggered accumulation results; A frequency estimation value updating module is used to determine a rough frequency estimation value based on the residual frequency offset estimation value and the initial frequency value; The secondary capture module is used to capture the spread spectrum signal again according to the rough frequency estimation value to obtain the code phase value output by the spread spectrum capture.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executes the method for real-time acquisition of spread spectrum signals according to any one of claims 1 to 7.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the program instructions are executed by a processor, they are used to implement the process corresponding to the method for real-time acquisition of spread spectrum signals according to any one of claims 1 to 7.

Images