Spread spectrum signal real-time capturing method and device, electronic equipment and storage medium

Abstract

The invention relates to the field of satellite communication, and provides a spread spectrum signal real-time capturing method and device, electronic equipment and a storage medium, and the spread spectrum signal real-time capturing method comprises the steps: traversing Doppler frequency shift gears to carry out spread spectrum signal capturing, and determining an initial code phase and an initial frequency value; window sliding frequency measurement is carried out in an adjacent chip range of the initial code phase, and a residual frequency offset estimation value is determined; determining a coarse frequency estimation value according to the residual frequency offset estimation value and the initial frequency value; and performing spread spectrum signal capture again according to the coarse frequency estimation value to obtain a code phase value output by spread spectrum capture. According to the method and the device, search of three dimensions of code phase, frequency and code Doppler is reduced into search of two dimensions of phase and frequency, the method and the device are closer to engineering application of satellite communication, the problem of signal capture under the condition of large code Doppler can be solved, and the memory space in an existing capture scheme can be greatly reduced.

Description

Technical Field

[0001] The present invention belongs to the fields of satellite communication and wireless communication, and particularly relates to a method, device, electronic device, and storage medium for real-time acquisition of spread-spectrum signals. Background Art

[0002] The acquisition of spread-spectrum signals is the first step in receiving and processing spread-spectrum signals and is an essential and important part of spread-spectrum signal processing. The main task of spread-spectrum signal acquisition is to perform coarse synchronization of code phase, time slot, and frequency on the baseband IQ data processed by the digital front end, create conditions for subsequent tracking, and reduce the time consumed by tracking. In current spread-spectrum signal acquisition schemes, compressive sensing methods and search methods using large-point FFT (Fast Fourier Transform) / IFFT (Inverse Fast Fourier Transform) are used to solve the problem of search speed. However, compressive sensing calculations and large-point FFT / IFFT often involve relatively complex mathematical operations, resulting in too high computational complexity, thereby increasing the consumption of computational resources and storage resources. Summary of the Invention

[0003] Embodiments of the present application provide a method, device, electronic device, and storage medium for real-time acquisition of spread-spectrum signals to solve the problem of too high computational complexity during the acquisition of spread-spectrum signals.

[0004] Other features and advantages of the present application will become apparent through the following detailed description, or will be partially learned through the practice of the present application.

[0005] According to a first aspect of the embodiments of the present application, a method for real-time acquisition of spread-spectrum signals is provided, including: traversing Doppler frequency offset gears to acquire spread-spectrum signals, and determining an initial code phase and an initial frequency value; performing window sliding frequency measurement within an adjacent chip range of the initial code phase to determine a residual frequency offset estimation value; determining a coarse frequency estimation value based on the residual frequency offset estimation value and the initial frequency value; and acquiring the code phase value output by spread-spectrum acquisition again based on the coarse frequency estimation value. The present application reduces the search in three dimensions of code phase, frequency, and code Doppler to two dimensions of phase and frequency for search, which is closer to the engineering application of satellite communication, can solve the problem of signal acquisition in the case of large code Doppler, and can significantly reduce the storage amount in the existing acquisition scheme.

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

[0007] In one embodiment of the present application, traversing the Doppler frequency offset gears to perform spread-spectrum signal acquisition and determining the initial code phase and the initial frequency value specifically includes: determining the number of time slots required for acquisition; under each Doppler gear, performing staggered accumulation on the data within the determined number of time slots, and selecting the maximum value in the staggered accumulation results as the correlation value corresponding to the gear; using the gear value corresponding to the maximum correlation value among all Doppler gears as the initial frequency value, and simultaneously determining the initial code phase value according to the position where the maximum correlation value is located.

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

[0009] In one embodiment of the present application, performing staggered accumulation on the data within the determined number of time slots and selecting the maximum value in the staggered accumulation results as the correlation value corresponding to the gear specifically includes: performing mixing, segmented accumulation, and correlation operations on the sampled data using the selected Doppler frequency offset gear value to obtain numerical sequence data; staggeredly selecting the numerical sequence data of each time slot based on the selected Doppler frequency offset gear value, and accumulating the staggered numerical sequence data of the selected time slots 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 offset gear, and recording its serial number in the staggered accumulation value sequence.

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

[0011] In one embodiment of the present application, performing spread-spectrum signal acquisition again according to the rough frequency estimation value to obtain the code phase value output by spread-spectrum acquisition includes: using the rough frequency estimation value as the frequency gear, staggeredly selecting the data of each time slot, and performing staggered accumulation, and using the position of the maximum value in the staggered accumulation results as the code phase value of spread-spectrum acquisition.

[0012] In one embodiment of the present application, the staggered accumulation specifically includes: calculating the staggered values of each time slot; the staggered values are determined by the number of chips in the time slot, the time slot number, the number of samples per chip, the relative motion speed between the satellite corresponding to the frequency gear and the receiving end, and the speed of light; staggeredly selecting the data of each time slot according to the staggered values.

[0013] According to a second aspect of the embodiments of the present application, a spread spectrum signal real-time capture device is provided, including: a primary capture module, configured to divide Doppler frequency offset ranges, traverse the Doppler frequency offset ranges to capture spread spectrum signals, and determine an initial code phase and an initial frequency value; a residual frequency offset estimation module, configured to perform window sliding frequency measurement within an adjacent chip range of the initial code phase to determine a residual frequency offset estimation value; a frequency estimation value update module, configured to determine a rough frequency estimation value based on the residual frequency offset estimation value and the initial frequency value; a secondary capture module, configured to capture spread spectrum signals again based on the rough frequency estimation value to obtain a code phase value output from spread spectrum capture.

[0014] According to a third aspect of the embodiments of the present application, an electronic device is provided, including a memory and a processor, and a computer program capable of being loaded and executed by the processor and corresponding to the spread spectrum signal real-time capture method described in the first aspect is stored on the memory.

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

[0016] The main solution of the present application and its various further alternative solutions can be freely combined to form multiple solutions, all of which are solutions that can be adopted and claimed in the present application. Those skilled in the art can understand that there are multiple combinations according to the prior art and common general knowledge after understanding the solution of the present application, and all of them are the technical solutions to be protected by the present application, and will not be enumerated here. Description of the Drawings

[0017] The drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

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

[0019] Figure 2 It is a flowchart of the spread spectrum signal real-time capture method according to the embodiments of the present application.

[0020] Figure 3 It is a schematic diagram of the spread spectrum signal real-time capture method according to the embodiments of the present application.

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

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

[0023] Figure 6 It is a simulation diagram of window search frequency measurement according to 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 schematic structural diagram of a computer system of an electronic device suitable for implementing the embodiments of the present application. Detailed implementation manners

[0026] To make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments.

[0027] Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present application. Without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other arbitrarily. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0028] The terms "including" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0029] "Multiple" in the present application may mean at least two, for example, it may be two, three or more, and the embodiments of the present application do not make limitations. In the technical solutions of the present application, the collection, dissemination, use, etc. of data all comply with the requirements of relevant national laws and regulations.

[0030] As Figure 1 shown, spread spectrum signal acquisition is a set of fully digital functions after the DFE (Decision Feedback Equalizer) and before spread spectrum tracking in the entire digital receiver. The current spread spectrum signal acquisition schemes mainly have the following problems: (1) High computational complexity. Most existing solutions require compressive sensing calculations. Compressive sensing methods need to sparsely represent and reconstruct the sampled data. Usually, sparse representation is performed through dictionary-based methods, such as sparse representation dictionaries, wavelet transforms, etc., which require complex matrix operations. The commonly used methods for reconstructing and recovering the original signal are usually optimization algorithms, such as least squares, iterative thresholding, etc., which involve matrix inversion, high-order matrix multiplication operations, and also involve multiple iterations. Or most existing solutions require multiple large-point FFTs, as well as large-point IFFTs, large-point FFT / IFFT. That is, the calculations in the existing technology involve relatively complex mathematical operations.

[0031] (2) Large computational storage overhead. Existing solutions need to collect and store data. For cases with low signal-to-noise ratio, the amount of data to be stored increases exponentially. For complex processing processes, temporary data generated during the calculation process also needs to be stored. Before traversing and searching all code phases and obtaining the code phase capture result, the collected data is still stored in the storage unit and cannot be released, resulting in inefficient reuse of storage resources and large storage overhead. And the storage required for subsequent tracking is small. The high storage space allocated specifically for capture, because the capture function is only enabled in a few scenarios such as initial access or tracking failure, the large storage space leads to low utilization rate of storage resources.

[0032] Based on this, the embodiments of the present application propose a method for real-time capture of spread spectrum signals. By reducing the search in three dimensions of code phase, frequency, and code Doppler to two dimensions of phase and frequency for search, and only using lower algorithm complexity operation methods such as correlation and accumulation operations, and a storage scheme based on gear-based misaligned accumulation results to overwrite the original data storage unit, the computational complexity and storage amount are greatly reduced, and excellent capture performance is achieved. Please refer to Figure 2 , and the specific solution is as follows: S100. Traverse the Doppler frequency offset gears to capture the spread spectrum signal, and determine the initial code phase and initial frequency value.

[0033] In this embodiment, by dividing the Doppler frequency offset into gears, the original three-dimensional search of code phase, frequency, and code Doppler is reduced to a two-dimensional search to achieve good capture performance. Therefore, when performing spread spectrum signal capture, first complete the division of Doppler frequency offset gears according to the maximum Doppler frequency offset of the carrier and the frequency division interval; among them, the frequency division interval is determined by the frequency offset corresponding to the signal peak dropping by a preset decibel during the signal capture simulation process.

[0034] Suppose the real-time received data stream signal is :

[0035] Among them, is the signal amplitude; The symbol for signal modulation; The pseudo-random code; The phase offset of the pseudo-code, The Doppler frequency offset of the carrier, ∆T is the sampling time interval, The Gaussian white noise.

[0036] Let the maximum Doppler frequency offset of the carrier be , the lowest signal-to-noise ratio be , the chip rate after spreading be , the baseband The data sampling rate is , the number of chips in one time slot is , the length of the primary synchronization code in one time slot is ; The capture success rate is ; The received radio frequency frequency point of the spread signal . At this time, according to the lowest signal-to-noise ratio , when the simulation only considers the frequency offset change factor, the segmented accumulation method is used to determine the frequency offset corresponding to the preset decibel drop compared to the peak, and then the number of Doppler frequency offset levels can be obtained.

[0037] After determining the Doppler frequency offset level, it is also necessary to determine the number of time slots required for signal capture, so as to determine the data length required for calculation. In this embodiment, according to the lowest signal-to-noise ratio , the number of time slots required to reach the capture success rate is obtained by using the segmented accumulation method when the simulation has no frequency offset, and then the number of time slots required for real-time capture is finally determined.

[0038] It should be noted that in this embodiment, the data in the time slot is processed by the segmented accumulation method to save storage space, as follows: Let the M sampling data in a certain time slot be , and the method of segmented accumulation processing of M data is:

[0039]

[0040] Among them, is the spreading code sequence, which is determined during the design of the spread spectrum communication system and is used as a known condition.

[0041] The final result of segmented accumulation , where the absolute value is calculated by an approximate method, that is: .

[0042] After determining the Doppler frequency offset gear and the number of time slots a two-dimensional search can be performed. Refer to Figure 3 . In this embodiment, first perform P times of coarse code Doppler search according to the determined P Doppler frequency offset gears, and then perform coarse capture confirmation. That is, under each Doppler gear, perform staggered accumulation on the data within the determined number of time slots, and select the maximum value in the staggered accumulation result as the correlation value corresponding to the gear; use the gear value corresponding to the maximum correlation value among all Doppler gears as the initial frequency value, and at the same time determine the initial code phase value according to the position where the maximum correlation value is located.

[0043] During the search process, by processing the data between time slots in a staggered accumulation manner and cooperating with the method of segment accumulation of data within a time slot, the storage capacity can be significantly reduced. Specifically, in this embodiment, the staggered accumulation process includes: performing mixing, segment accumulation, and correlation operations on the sampled data using the selected Doppler frequency offset gear value to obtain numerical sequence data; staggeredly selecting the numerical sequence data of each time slot based on the selected Doppler frequency offset gear value, and accumulating the staggered numerical sequence data of the selected time slots to obtain a staggered accumulation value sequence; using the maximum value in the staggered accumulation value sequence as the correlation value of this Doppler frequency offset gear, and recording its serial number in the staggered accumulation value sequence, where the serial number can be used to determine the initial code phase value.

[0044] This application calculates the number of staggered sampling points between time slots according to the code Doppler gear situation, realizes staggered accumulation between time slots, and significantly 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 process of performing staggered accumulation, the staggered value used is:

[0045] where represents the number of chips in one time slot, represents the number of time slots corresponding to real-time capture, represents the time slot number, represents the number of sampling points per chip, represents the relative motion speed of the user terminal and the satellite corresponding to the frequency gear. Based on the staggered values corresponding to each time slot, the data is staggeredly selected, and the subsequent staggered selection data is accumulated to complete the staggered accumulation process.

[0046] Assume that each chip samples I data points. Taking the case of no Doppler shift as an example, there is no code Doppler at this time, and the staggered accumulation is reflected in the following three-row vector, where each row +1 points are added correspondingly. When implemented in hardware, only the cumulative result needs to be stored. When a new packet of data arrives, perform three steps: read the cumulative result, add it to the new data, and store the cumulative result.

[0047]

[0048] …

[0049] After corresponding addition, we get +1 numbers as follows:

[0050]

[0051] … .

[0052] Due to the large signal dynamics, the code phase value after multi-gear search may have a large drift due to code Doppler. To reduce the complexity of subsequent frequency measurement and search, please continue to refer to Figure 3 , in this embodiment, perform a search once (i.e., rough capture confirmation) with the determined initial frequency value as the only gear value, re-determine the code phase value, and use this code phase value as the final initial code phase.

[0053] Through the acquisition 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 acquired code phase within several clock cycles after the last data input participating in the acquisition operation, and the acquisition has good real-time performance; the data participating in the misalignment accumulation operation is obtained by the parallel correlation method from the baseband IQ data, and the parallel correlation operation only involves addition and subtraction operations, which is realized by engineering.

[0054] S200. Perform window sliding frequency measurement in the adjacent chip range of the initial code phase to determine the residual frequency offset estimation value.

[0055] There may be a residual frequency offset estimation value that has not been obtained during the first acquisition process. Please continue to refer to Figure 3 , in this embodiment, the window sliding frequency measurement method is used to obtain the residual frequency offset estimation value for subsequent determination of the rough frequency estimation value. Specifically, first, based on the initial frequency value, misalign and select the misaligned data of the required time slots corresponding to the initial code phase and the code phase sampling points within the adjacent chip range; then, for the misaligned data corresponding to each code phase, perform segmented accumulation within the time slot, FFT processing, take the absolute value, and accumulate between time slots to obtain the maximum value of the misaligned accumulation results corresponding to each code phase; finally, determine the residual frequency offset estimation value according to the position of the maximum value among the maximum values of the misaligned accumulation results. The principle of segmented accumulation and misaligned accumulation used in the window sliding frequency measurement process is similar to that in S100, and will not be elaborated here.

[0056] S300. Determine the rough frequency estimate value based on the residual frequency offset estimate value and the initial frequency value.

[0057] In this step, the rough frequency estimate value can be obtained by superimposing the residual frequency offset estimate value on the initial frequency value, completing the initial capture.

[0058] S400. Perform spread spectrum signal capture again according to the rough frequency estimate value to obtain the code phase value output by the spread spectrum capture.

[0059] Please continue to refer to Figure 3 , finally, taking the rough frequency estimate value as the frequency gear, perform spread spectrum signal capture again (i.e., the (P + 1)-th 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 of S100, that is, misaligned accumulation is performed on the data within the determined number of time slots, and the position of the maximum value in the misaligned accumulation result is selected to determine the code phase value of the spread spectrum capture.

[0060] In view of the signal capture problem of the satellite communication spread spectrum system, under the conditions of many adverse influencing factors such as large frequency Doppler dynamics, large code Doppler change range, and low signal-to-noise ratio, through careful analysis of the inertial change law of the code Doppler and the initial capture index, an optimized algorithm is designed. Only through relatively low algorithm complexity operation methods such as correlation and accumulation operations, and a storage scheme based on the misaligned accumulation result covering the original data storage unit, the computational complexity and storage volume are greatly reduced, and excellent capture performance is achieved.

[0061] Compared with the existing spread spectrum capture technology, the technical solution of the present application is closer to the engineering application of satellite communication, can solve the signal capture problem in the case of large code Doppler, can greatly reduce the storage volume in the existing capture scheme, and the calculation method only involves mixing and correlation operations, which can be realized by engineering. The present application reduces the search in three dimensions of code phase, frequency, and code Doppler to two dimensions of phase and frequency for search; this scheme greatly compresses the consumption of the overall storage resources, and the main operations are correlation, mixing, and accumulation, which can be well designed into a hardware circuit. Since the operation method is simple, the gear search time can be greatly reduced by a parallel method, and the adaptability is stronger, which is more applicable in actual engineering.

[0062] To better understand the spread spectrum signal capture method proposed in the present application, the following specifically describes a scenario where the chip rate is 5 Mcps, the sampling rate of the baseband IQ data is 10 MHz, there are 6000 chips in one time slot, the length of the primary synchronization code in one time slot is 500, the minimum signal-to-noise ratio required for capture is -23 dB, the maximum Doppler is 40 kHz, the signal radio frequency is 1.5 GHz, and the capture success rate is over 90%. The signal structure is as Figure 4 shown.

[0063] Through simulation, it is determined that when SNR_MIN = -23 dB, the number of time slots required for the segmented accumulation method to achieve a 90% capture success rate is approximately 15. In the case of no noise, the accumulated peak corresponding to 15 time slots is approximately 7500. When the peak drops by 3 dB, that is, when the value is around 3750, the corresponding frequency offset is approximately 5 kHz. Therefore, the Doppler is divided into 40 2 / 5 + 1 = 17 gears, and the number of time slots is set to 30. The number of sampling points corresponding to 6000 code phases in one time slot is 6000 10e6 / 5e6 = 12000.

[0064] Taking the Doppler corresponding to 40 kHz as an example, the corresponding 30 dislocation values are round(8e3 / 3e8 2 6000 (0:29)), as shown in Table 1 specifically.

[0065] Table 1

[0066] For the continuous sequence of sampled data, mix it according to the frequency offset of 40 kHz to obtain a sequence , and calculate the numerical sequence in real time according to the subsequent rules

[0067] for dislocation accumulation. Specifically as follows: First is the register maintenance. Since the oversampling multiple is 2, two groups of registers need to be maintained. Let the sampled data be in chronological order: .

[0068] The first group of registers: . The second group of registers: .

[0069] After a new data comes in, if the data is , then update the value of the first register to: .

[0070] If the data is , then update the value of the second group of registers to: .

[0071] Secondly is the digital calculation. Before a new sampling point comes, it is necessary to complete the accumulation processing of 500 data in , that is:

[0072]

[0073] Segmented accumulation result , where the absolute value is calculated using an approximation method, i.e., .

[0074] The method of staggered accumulation calculation is as follows: Suppose the correlated sequence is in turn according to the sampling serial number as:

[0075] .

[0076] When there is no code Doppler, there is no need for staggering in each time slot. After staggering the data of 30 time slots, the sliding window sequence (i.e., the obtained staggered accumulation value sequence) Is obtained by adding the following 30 vectors correspondingly:

[0077]

[0078]

[0079]

[0080] One more sampling point in the sliding window is considered because the code Doppler may shift one sampling point within a time slot. When the offset value of each time slot caused by the code Doppler is (Obtained by looking up Table 1 according to the time slot number), the sliding window sequence (i.e., the obtained staggered accumulation value sequence) Is obtained by adding the following 30 vectors correspondingly:

[0081]

[0082]

[0083]

[0084] Considering the staggered value The maximum value of is 9 and the increase in the sliding window length caused by the code Doppler. In order for the staggered accumulation to proceed normally, the required data volume in addition to 30 6000 2 (i.e., ), may also involve And , ,…, A total of 18 correlation values. Therefore, if 6000 If two sampling points form one time slot, then to complete the search for one gear, 32 time slots need to be spanned. However, for real-time calculation, in this embodiment, only 9 correlation values need to be added before and after, for a total of 18 added correlation values.

[0085] For the 40kHz frequency offset gear, after 30 time slots of misaligned accumulation, a sequence of misaligned accumulation values can be obtained A total of 12001 correlation values. Take the maximum value among the 12001 values as the correlation value of this gear, and record the serial number corresponding to the maximum value.

[0086] Calculate the correlation values for 17 gears respectively , take the frequency gear value corresponding to the maximum value as the initial frequency estimate value , take the serial number value corresponding to this gear as the initial code phase .

[0087] Due to the large signal dynamics, the code phase value after completing the multi-gear search may have a large drift due to code Doppler. To reduce the complexity of subsequent frequency measurement and search, after determining the initial frequency estimate value and the initial code phase, a rough capture confirmation is required. That is, according to the initial frequency estimate value as the only gear value, a search is carried out once. The search process is exactly the same as the process of the aforementioned 17 gears, except that there is only one gear, and the final initial frequency estimate value and the initial code phase are obtained.

[0088] 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 value, that is, calculate the misaligned value It is:

[0089] Among them, represents the relative motion speed between the user terminal and the satellite corresponding to the Doppler frequency offset gear, which corresponds to the initial frequency estimate value. Then, taking the initial code phase as the reference value, extract the PSC (Primary Synchronization Code) data of 30 time slots:

[0090] It should be noted that the PSC data here is the data that has been misaligned and selected through the misaligned value.

[0091] For every 500 data of each segment, they are evenly divided into 50 segments in order, with 10 data in each segment. Sum the 10 data in each segment to obtain 50 data. Perform a 1024-point FFT on the 50 data and take the absolute value to obtain 1024 spectral results:

[0092] Add them correspondingly to obtain 1024 data , where:

[0093] From find the maximum value , and the subscript of the maximum value is .

[0094] Take two sampling points respectively in adjacent code chips of the initial code phase and perform the same operation, that is, repeat taking the PSC data of 30 time slots for calculation to obtain the under 5 sampling points, determine the maximum value among them, and output the subscript corresponding to the maximum value , and obtain the residual frequency offset estimation value: . Finally, the rough frequency estimation value output by the spread spectrum acquisition is .

[0095] Finally, set the frequency gear value to , and perform the same process of acquisition confirmation again to estimate the rough code phase estimation value , which is used as the code phase value output by the spread spectrum acquisition. The processing result is output within several clock cycles after the last data participating in the operation.

[0096] In order to further verify the method proposed in this application, the code phase is randomly configured between [1 - 6000], and the frequency offset is randomly configured between -40 kHz and 40 kHz. Run the method provided in this application multiple times through simulation. The criterion for successful acquisition is that the code phase does not exceed half a code chip from the set value, and the criterion for successful frequency offset estimation is that the frequency error does not exceed half of the gear interval. The statistical results are as follows: ESNO = -23 dB, 30 slots, random time offset, random frequency offset, run 30000 times, acquisition success rate 94.8%, frequency offset measurement success rate 94.72%, and the performance meets the design requirements.

[0097] The single simulation, gear search simulation and window search frequency measurement results are respectively as Figure 5 and Figure 6 shown. It can be seen from the figure that under the conditions of this random simulation, a peak appears in the 15th gear, and the corresponding Doppler frequency offset is 32 kHz. When performing window search frequency measurement, within the window with a window length of 5, a peak appears in the third window, so the frequency result measured by the third window is taken.

[0098] The embodiment of the present application also provides a spread spectrum signal real-time capture device, including: a primary capture module, configured to divide Doppler frequency offset levels, traverse the Doppler frequency offset levels to capture spread spectrum signals, and determine an initial code phase and an initial frequency value; a residual frequency offset estimation module, configured to perform window sliding frequency measurement within an adjacent chip range of the initial code phase to determine a residual frequency offset estimation value; a frequency estimation value update module, configured to determine a rough frequency estimation value according to the residual frequency offset estimation value and the initial frequency value; a secondary capture module, configured to capture spread spectrum signals again according to the rough frequency estimation value to obtain a code phase value output by spread spectrum capture.

[0099] The following introduces the electronic device embodiment of the present application, which can be used to execute the high-precision frequency offset estimation method in the above embodiments of the present application. For details not disclosed in the electronic device embodiment, please refer to the method embodiments of the present application above.

[0100] Refer to Figure 7 As shown in the figure, an electronic device 500 according to an embodiment of the present application includes: a memory 501 and a processor 502. A computer program corresponding to the spread spectrum signal real-time capture method described in the first aspect is stored on the memory 501 and can be loaded and executed by the processor 502.

[0101] Figure 8 The figure shows a schematic structural diagram of a computer system of an electronic device suitable for implementing the embodiments of the present application.

[0102] It should be noted that Figure 8 The computer system 600 of the electronic device shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present application.

[0103] As Figure 7 shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 602 or the program loaded from the storage section 608 into the random access memory (RAM) 603, such as executing the method described in the above embodiments. In the RAM 603, various programs and data required for system operation are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other through a bus 604. The input / output (I / O) interface 605 is also connected to the bus 604.

[0104] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. 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 required. A removable storage medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as required so that a computer program read therefrom is installed into the storage section 608 as required.

[0105] Specifically, according to an embodiment of the present application, the processes described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product that includes a computer program carried on a computer-readable medium, and the computer program includes program codes for performing the methods shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 609, and / or installed from the removable storage medium 611. When the computer program is executed by a central processing unit (CPU) 601, various functions defined in the system of the present application are executed.

[0106] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. In the present application, the computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and this computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0107] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. Among them, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code, and the above module, program segment, or part of 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 blocks may occur in a different order from that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0108] The units involved in the embodiments described in this application can be implemented in software or in hardware, and the described units can also be provided in a processor. Among them, the names of these units do not, in some cases, constitute a limitation on the units themselves.

[0109] As another aspect, the present application also provides a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the spread spectrum signal real-time capture method described in the above embodiments.

[0110] As another aspect, the present application also provides a computer-readable medium. The computer-readable medium can be included in the electronic device described in the above embodiments; it can also exist alone without being assembled into the electronic device. The above computer-readable medium carries one or more programs. When the above one or more programs are executed by an electronic device, the electronic device implements the spread spectrum signal real-time capture method described in the above embodiments.

[0111] It should be noted that although several modules or units of a device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of the two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0112] Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented by software or by a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present application can be embodied in the form of a software product. The software product 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 several 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.

[0113] For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances; the accompanying 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 part of the embodiments of the present invention, rather than all of the embodiments. Generally, the components of the embodiments of the present invention described and illustrated herein can be arranged and designed in various different configurations.

[0114] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

[0115] The foregoing is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A real-time acquisition method for spread-spectrum signals, characterized in that, Including: Traverse Doppler frequency offset levels to perform spread-spectrum signal acquisition, and determine the initial code phase and initial frequency value; Perform window sliding frequency measurement within the adjacent chip range of the initial code phase to determine the residual frequency offset estimation value; Determine the rough frequency estimation value according to the residual frequency offset estimation value and the initial frequency value; Perform spread-spectrum signal acquisition again according to the rough frequency estimation value to obtain the code phase value output by spread-spectrum acquisition.

2. The real-time acquisition method of the spread spectrum signal according to claim 1, characterized in that The Doppler frequency offset levels are divided according to the maximum Doppler frequency offset of the carrier and the frequency bin interval; wherein, the frequency bin interval is determined by the frequency offset corresponding to the signal peak dropping by a preset decibel during the signal acquisition simulation process.

3. The real-time acquisition method of the spread spectrum signal according to claim 1, characterized in that, The traversing the Doppler frequency offset levels to perform spread-spectrum signal acquisition and determining the initial code phase and initial frequency value specifically includes: Determine the number of time slots required for acquisition; Under each Doppler level, perform staggered accumulation on the data within the determined number of time slots, and select the maximum value in the staggered accumulation result as the correlation value corresponding to the level; Take the level value corresponding to the maximum correlation value among all Doppler levels as the initial frequency value, and at the same time determine the initial code phase value according to the position where the maximum correlation value is located.

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

5. The real-time acquisition method of the spread spectrum signal according to claim 3, characterized in that The performing staggered accumulation on the data within the determined number of time slots and selecting the maximum value in the staggered accumulation result as the correlation value corresponding to the level specifically includes: Mix the sampled data using the selected Doppler frequency offset level value, perform segmented accumulation and correlation operations to obtain numerical sequence data; staggeredly select the numerical sequence data of each time slot based on the selected Doppler frequency offset level value, and accumulate the staggered numerical sequence data of the selected time slots to obtain a staggered accumulation value sequence; Take the maximum value in the staggered accumulation value sequence as the correlation value of this Doppler frequency offset level, and record its serial number in the staggered accumulation value sequence.

6. The real-time acquisition method of the spread spectrum signal according to claim 1, characterized in that, The performing window sliding frequency measurement within the adjacent chip range of the initial code phase to determine the residual frequency offset estimation value specifically includes: Staggeredly select the staggered data of the required time slots corresponding to the code phase sampling points within the initial code phase and the adjacent chip range based on the initial frequency value; For the staggered data corresponding to each code phase, perform segmented accumulation within the time slot, take the absolute value after FFT processing, and accumulate between time slots to obtain the maximum value of the staggered accumulation result corresponding to each code phase; Determine the residual frequency offset estimation value according to the position of the maximum value among the maximum values of each staggered accumulation result.

7. The real-time acquisition method of the spread spectrum signal according to claim 1, characterized in that The performing spread-spectrum signal acquisition again according to the rough frequency estimation value to obtain the code phase value output by spread-spectrum acquisition includes: Take the rough frequency estimation value as the frequency level, staggeredly select the data of each time slot, and perform staggered accumulation. Take the position of the maximum value in the selected staggered accumulation result as the code phase value of spread-spectrum acquisition.

8. The real-time acquisition method of the spread spectrum signal according to claim 3, 6 or 7, characterized in that The staggered selection of data includes: Calculate the staggered value of each time slot; the staggered value is determined by the number of chips in the time slot, the time slot number, the number of single-chip sampling points, the relative motion speed between the satellite corresponding to the frequency level and the receiving end, and the speed of light; Staggeredly select the data of each time slot according to the staggered value.

9. A real-time acquisition device for spread-spectrum signals, characterized in that, Including: A primary capture module, which is used to divide Doppler frequency offset gears, traverse the Doppler frequency offset gears to perform spread-spectrum signal capture, and determine an initial code phase and an initial frequency value; A residual frequency offset estimation module, which is used to perform window sliding frequency measurement within the adjacent chip range of the initial code phase to determine a residual frequency offset estimation value; A frequency estimation value update module, which is used to determine a rough frequency estimation value according to the residual frequency offset estimation value and the initial frequency value; A secondary capture module, which is used to perform spread-spectrum signal capture again according to the rough frequency estimation value to obtain a code phase value output by spread-spectrum capture.

10. An electronic device, characterized in that, It includes a memory and a processor, and a computer program corresponding to the spread-spectrum signal real-time capture method according to any one of claims 1 to 8 is stored on the memory and can be loaded and executed by the processor.

11. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the program instructions are executed by the processor, they are used to implement the process corresponding to the spread-spectrum signal real-time capture method according to any one of claims 1 to 8.

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