A fast acquisition method for weak signal GNSS receiver
By chunking and downsampling the GNSS receiver intermediate frequency signal, and combining FFT transformation and Doppler shift signal mixed operation, the problems of algorithm complexity and time power consumption in the capture stage in the prior art are solved, and efficient signal capture and accurate Doppler shift resolution are achieved.
Patent Information
- Application Number
- CN202111225504.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-01-20
- Publication Date
- 2025-04-18
- Estimated Expiration
- 2042-01-20
AI Technical Summary
The prior art is difficult to improve Doppler shift resolution and signal-to-noise ratio while reducing algorithm complexity and time and power consumption in the GNSS receiver capture stage.
By reading the intermediate frequency signal data of an integer multiple of the pseudocode period, data blocking and downsampling are performed, and combined with the mixed operation of FFT transformation and Doppler shift signals, the rapid capture and precise positioning of the signal are achieved.
It is realized that the Doppler shift resolution and signal-to-noise ratio are improved without increasing the computing volume, the time and power consumption of the capture stage are reduced, and the overall operating efficiency is improved.
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Figure CN114114335B_ABST
Abstract
Description
Technical Field
[0001] The invention relates to a method for fast capturing a weak signal GNSS receiver, and belongs to a baseband processing part in the field of satellite navigation. Background Art
[0002] The global satellite navigation system (GNSS) is increasingly used in military and civilian fields, including transportation, agriculture, forestry, fishery, weapons and equipment and other professional fields. Billions of smart products and devices are integrated with GNSS technology. Signal capture is the first step in signal processing in satellite signal receivers. Only after signal capture can a series of signal processing processes such as signal tracking be started, and finally the position velocity solution (PVT) function is completed. Due to the tens of millions to billions of digital multiplications caused by the three-dimensional search in the capture stage, the satellite signal is very weak, and it is often necessary to extend the length of the captured data, that is, to increase the coherent integration time and the number of accumulations. In addition, many devices that support GNSS have strict battery capacity limitations. Therefore, reducing the algorithm complexity of the capture stage and reducing the time spent in the capture stage and the power consumption it occupies are the key to the baseband processing part of the GNSS receiver.
[0003] Since Van Nee proposed the parallel frequency / code phase search algorithm based on FFT / IFFT, FFT operation has become the core of realizing fast satellite signal acquisition. Signal acquisition is mainly realized by using the strong autocorrelation of pseudo-random noise code (PRN) in code division multiple access (CDMA) system. Based on the relationship between discrete Fourier transform (DFT) and signal convolution, that is, the convolution in the time domain corresponds to the multiplication in the frequency domain, the signal convolution in the time domain in the autocorrelation function can be converted into the multiplication in the frequency domain, and the fast Fourier transform (FFT) algorithm can be used to greatly reduce the amount of calculation. The subsequent radix 4-FFT and split radix FFT acquisition algorithms proposed by Rao et al. have improved the efficiency of related operations in the acquisition process and relaxed the restrictions on the initial sampling frequency. However, the overall complexity of these improved FFT algorithms is still based on the product of the number of points and the logarithm of the number of points as the asymptotic upper limit, and there is no obvious improvement in acquisition performance or operation time. The sparse Fourier transform (SFT) proposed by Hassanieh realizes sublinear processing of the acquisition algorithm. Due to the accumulation of larger phase shifts on the samples, the Doppler frequency shift resolution is reduced, but the application of its sparsity idea in the acquisition field can greatly reduce the amount of calculation.
[0004] In recent years, the sparse characteristics of signals have been widely used in various researches due to their good performance in reducing the amount of computation. Satellite signals have only one peak after successful capture, so the amount of computation can be better reduced by applying sparsity. However, on the one hand, the use of sparsity will make the signal power sensitive to the error of the carrier frequency, and the Doppler search frequency needs to be refined. On the other hand, for weak signals, the integration time should be extended to enhance the signal-to-noise ratio. Therefore, it is necessary to study a fast capture algorithm that can increase the coherent integration time and refine the Doppler frequency shift resolution. Summary of the invention
[0005] The technical problem to be solved by the present invention is to provide a method for rapid acquisition of a weak signal GNSS receiver, which can select a suitable downsampling factor and number of data blocks under various environmental conditions to complete the rapid acquisition of satellite signals, thereby reducing the overall amount of calculation, maintaining the accuracy, and reducing the time and power consumption spent in the overall acquisition stage.
[0006] In order to solve the above technical problems, the present invention provides a method for fast acquisition of a weak signal GNSS receiver, the method comprising the following steps:
[0007] (1) Read the intermediate frequency signal data to be processed that is an integer multiple of the pseudo code period and does not exceed the navigation message bit jump period;
[0008] (2) mixing the data read in step (1) with the output signal of the local carrier generator, and obtaining a baseband complex signal through a low-pass filter;
[0009] (3) dividing the baseband complex signal obtained in step (2) into blocks according to the pseudo code period into a two-dimensional matrix form;
[0010] (4) setting a downsampling factor to alias each data block of the two-dimensional matrix obtained in step (3);
[0011] (5) performing FFT transformation on each vertical block of the two-dimensional matrix obtained in step (3) to achieve frequency compensation so as to enhance the signal-to-noise ratio of the superimposed signal;
[0012] (6) The pseudo code signal output by the local pseudo code generator is mixed with the Doppler frequency shift signal by the same downsampling factor as in step (4), and then FFT transformation is performed and conjugate is taken;
[0013] (7) performing FFT transformation on each data block after aliasing in step (4), multiplying the result with the result of step (6), performing IFFT transformation and taking the modulus;
[0014] (8) Perform threshold judgment on the result of step (7), perform inverse aliasing operation on the pseudo code phase basket with peaks exceeding the threshold value, and obtain p pseudo code phase values. Perform correlation operation on these p pseudo code phase values and the complex signal under the searched Doppler frequency shift, and the pseudo code phase point corresponding to the maximum correlation value is the pseudo code phase that is accurately captured; if no peak exceeding the threshold value appears, reset the Doppler frequency shift signal of step (6) to the next search frequency point, and repeat steps (6) and (7).
[0015] Furthermore, in step (3), the two-dimensional matrix after data block division is L horizontal blocks and N vertical blocks, each horizontal block has N data representing sampled data within a pseudo code period, each vertical block has L data, and the sampling interval between data is one pseudo code period. For the i-th vertical block, ignoring the noise term, the mathematical expression s(·) of each point is:
[0016]
[0017] In the formula, C k is the pseudo-random noise code of satellite k, which is a periodic function; D k is the navigation message of satellite k, and is a constant when the length of the read data does not exceed the bit jump period; f k is the carrier frequency of satellite k. Affected by Doppler frequency shift, the carrier frequency of each satellite is different. s is the sampling period; is the initial carrier phase, and j is the imaginary unit.
[0018] Furthermore, in step (4), after aliasing each horizontal block of data, the mathematical expression for the i-th vertical block becomes:
[0019]
[0020] In the formula, the downsampling factor is Take an integer; B = N / p, which is the number of data baskets after aliasing; a is the data selection factor, a = 0, 1, ..., p-1; the sampling frequency of the vertical block is f p , that is, the pseudo code frequency, whose value is the inverse of the pseudo code period. If the carrier frequency is divided into f p The integer multiple and remainder of
[0021] f k =Ff p +Δf k (3)
[0022] Where F is an integer, 0<Δf k <f p , then the sampling point of the i-th vertical block is expressed as:
[0023]
[0024] Furthermore, in step (5), the result of performing FFT transformation on the i-th vertical block is:
[0025]
[0026] In the formula, the data of the i-th vertical block is replaced by Y(i,m), ω m is the refined angular frequency, ω m =2πmf p / L, m=0,1,…,L-1, Δω is Δf k The corresponding angular frequency, Δω=2πΔf k , at this time the data of the mth horizontal block is:
[0027]
[0028] At the sampling time of the mth horizontal block data, A(m) is a common item that is independent of the sampling time, and its modulus is expressed as:
[0029]
[0030] When Δω=ω m When , formula (7) takes the maximum value L, the data can be accumulated to increase the signal-to-noise ratio by 10lgL decibels.
[0031] The beneficial effects of the present invention are as follows: the Doppler frequency shift resolution can be determined according to the pseudo code period and the number of data blocks, the Doppler frequency shift search resolution can be refined to 1 / LkHz without introducing additional computational complexity; the signal-to-noise ratio can be increased by 10lgL dB by accumulating the signal after phase compensation, and the increase value is determined by the number of data blocks; the computational complexity of the overall capture stage can be reduced to 20LBlog2B+BLlog2L+2BL+2N, and when the sampling frequency is fixed, the overall computational complexity is jointly determined by the downsampling factor p and the number of data blocks L; and the overall operating efficiency can be improved while ensuring that the capture sensitivity remains unchanged. BRIEF DESCRIPTION OF THE DRAWINGS
[0032] Figure 1 A schematic flow chart of the method of the present invention;
[0033] Figure 2 Data sampling diagram;
[0034] Figure 3 Schematic diagram of two-dimensional rearrangement of intermediate frequency sampling data;
[0035] Figure 4 Schematic diagram of two-dimensional aliasing arrangement of intermediate frequency sampling data;
[0036] Figure 5Schematic diagram of horizontal block data capture;
[0037] Figure 6 Theoretical operation amount curve, Figure 6 (a) is a graph showing the amount of computation changing with the number of blocks, and (b) is a graph showing the amount of computation changing with the downsampling factor;
[0038] Figure 7 The final capture result diagram of the present invention is as follows: Figure 7 (a) is the result diagram of the FFT capture algorithm, (b) is the result diagram of the SFT capture algorithm, and (c) is the result diagram of the capture algorithm proposed in the present invention. DETAILED DESCRIPTION
[0039] like Figure 1 As shown, a method for fast acquisition of a weak signal GNSS receiver comprises the following steps:
[0040] (1) Read the intermediate frequency signal data to be processed that is an integer multiple of the pseudo code period and does not exceed the navigation message bit jump period;
[0041] (2) Mixing the intermediate frequency signal of step (1) with the sine carrier and cosine carrier output by the local carrier generator to obtain in-phase and quadrature branches, and obtaining a baseband complex signal by passing the in-phase branch as the real part and the quadrature branch as the imaginary part through a low-pass filter.
[0042] (3) dividing the baseband complex signal into blocks according to the pseudo code period into a two-dimensional matrix form;
[0043] (4) taking a suitable downsampling factor to perform aliasing on each data block of the two-dimensional matrix;
[0044] (5) Performing FFT transformation on each vertical block of the two-dimensional matrix to achieve frequency compensation to enhance the signal-to-noise ratio of the superimposed signal;
[0045] (6) Mix the local pseudo code with the Doppler frequency shift signal after aliasing according to step (4), perform FFT transformation and take the conjugate;
[0046] (7) performing FFT transformation on each data block, multiplying the result with the result of step (6), performing IFFT transformation and taking the modulus;
[0047] (8) Perform threshold judgment on the result of step (7), perform inverse aliasing operation on the pseudo code phase basket with peaks exceeding the threshold value, and obtain p possible pseudo code phase values. Perform correlation operation on these p pseudo code phase values and the complex signal under the searched Doppler frequency shift, and the pseudo code phase point corresponding to the maximum correlation value is the exact captured pseudo code phase; if there is no peak exceeding the threshold, reset the Doppler frequency shift signal in step (6) to an integer multiple of the pseudo code period within the overall search range, and repeat steps (6) and (7) until the search is successful or exceeds the search range.
[0048] In step (1), data of L times pseudo code period length is sampled, and the data sampling is as follows: Figure 2 .
[0049] In step (3), the two-dimensional rearrangement matrix after data block division is L horizontal blocks and N vertical blocks. Each horizontal block has N data representing the sampled data within a pseudo code period, and each vertical block has L data. The sampling interval between data is one pseudo code period. For the i-th vertical block, ignoring the noise term, the mathematical expression s(·) of each point is:
[0050]
[0051] In the formula, C k is the pseudo-random noise code of satellite k, which is a periodic function; D k is the navigation message of satellite k, and is a constant when the length of the read data does not exceed the bit jump period; f k is the carrier frequency of satellite k. Affected by Doppler frequency shift, the carrier frequency of each satellite is different. s is the sampling period; is the initial carrier phase.
[0052] In step (4), after aliasing each data block, the intermediate frequency sampling data is arranged in two dimensions as follows: Figure 4 , for the i-th vertical block, its mathematical expression becomes:
[0053]
[0054] In the formula, the downsampling factor is Take an integer, B = N / p, which is the number of data baskets after aliasing. a is the data selection factor, a = 0, 1, ..., p-1; the sampling frequency of the vertical block is f p , that is, the pseudo code frequency, whose value is the inverse of the pseudo code period. If the carrier frequency is divided into f p The integer multiple and remainder of
[0055] f k =Ff p +Δf k (3)
[0056] Where F is an integer, 0<Δf k <f p , then the sampling point of the i-th vertical block can be expressed as:
[0057]
[0058] In step (5), the result of performing FFT on the i-th vertical block is:
[0059]
[0060] In the formula, the data of the i-th vertical block is replaced by Y(i,m), ω m is the refined angular frequency, ω m =2πmf p / L, m=0,1,…,L-1, Δω is Δf k The corresponding angular frequency, Δω=2πΔf k ,like Figure 5 , at this time the data of the mth horizontal block is:
[0061]
[0062] At the sampling time of the mth horizontal block data, A(m) is a common item that is independent of the sampling time, and its modulus can be expressed as:
[0063]
[0064] When Δω=ω m When , formula (7) takes the maximum value L, the data can be accumulated to increase the signal-to-noise ratio by 10lgL decibels.
[0065] In step (6), the same downsampling factor p as in step (4) is used to alias the local pseudo code in the same manner, and the Doppler frequency shift search range is determined by mixing it with the Doppler frequency shift signal, performing an FFT operation and taking the conjugate.
[0066] In step (7), Figure 5 The method of using FFT to capture the mth horizontal block can obtain the calculation results of all pseudo code phase correlation. The only difference is that there is an additional common factor A(m) in the intermediate frequency data involved in the correlation operation. The A(m) corresponding to each horizontal block is the carrier frequency f k Medium pseudo code frequency f p The frequency selection factor in the following part refines the Doppler frequency resolution, and the frequency search granularity becomes f p / L, and f k Medium p The part, that is, the integer F in formula (3) and the Doppler frequency shift signal in step (6), is determined by setting the local carrier frequency when performing FFT capture on the horizontal block data.
[0067] The feasibility of the present invention is verified by the following experiments:
[0068] (1) The experiment uses real data collected by the UTK210A satellite intermediate frequency signal acquisition system to perform semi-physical simulation. The data is collected on an unobstructed rooftop. The simulation parameters are shown in Table 1.
[0069] Table 1 Simulation parameters
[0070]
[0071] (2) The satellite intermediate frequency signal acquisition system is a dual-mode system. The GPS signal is selected for simulation. Since the number of data blocks L is 2, the frequency search step is 500 Hz, the signal length T is 2 ms, and the downsampling factor p is 2. Each pseudo-code phase basket after aliasing corresponds to two pseudo-code phase points.
[0072] (3) For all simulations, the FFT operation after the mixed signal of the local pseudo code and the carrier is stored in advance, and directly extracted during capture to save this part of the computational complexity. The algorithm proposed in the present invention reduces the computational complexity required in the capture stage to 20LBlog2B+BLlog2L+2BL+2N. Figure 6 The results of the comparison of the computational complexity of the traditional FFT and SFT capture algorithms and the algorithm proposed in this invention are shown.
[0073] Semi-physical simulation experiments capture results such as Figure 7 , the experimental data is compared with Table 2. It can be seen that the initial pseudo code phase output by SFT and the algorithm proposed in the present invention is 520. Due to aliasing, the other pseudo code phase corresponding to this point is 8704. The correlation values of the two pseudo code phase points are calculated respectively. The correlation value at 8704 code bits is much larger than the correlation value at 520. The final pseudo code phase of 8704 is the same as the result of the FFT algorithm.
[0074] Table 2 Simulation data comparison
[0075]
[0076] Compared with the acquisition algorithms based on FFT and SFT, the signal-to-noise ratio of the algorithm proposed in the present invention is slightly reduced. At the same time, the computational efficiency of the algorithm proposed in the present invention is greatly increased. The computational time is reduced by 4.1 times compared with the acquisition algorithm based on FFT, and is reduced by 1.7 times compared with the acquisition algorithm based on SFT, which can better meet the performance requirements of the receiver.
[0077] As described above, although the present invention has been shown and described with reference to specific preferred embodiments, it should not be construed as limiting the present invention itself. Various changes in form and details may be made without departing from the spirit and scope of the present invention as defined in the appended claims.
Claims
1. A method for fast acquisition of a weak signal GNSS receiver, characterized in that: The method comprises the following steps: (1) Read the intermediate frequency signal data to be processed that is an integer multiple of the pseudo code period and does not exceed the navigation message bit jump period; (2) mixing the data read in step (1) with the output signal of the local carrier generator, and obtaining a baseband complex signal through a low-pass filter; (3) dividing the baseband complex signal obtained in step (2) into blocks according to the pseudo code period into a two-dimensional matrix form; (4) setting a downsampling factor to alias each data block of the two-dimensional matrix obtained in step (3); (5) performing FFT transformation on each vertical block of the two-dimensional matrix obtained in step (3) to achieve frequency compensation so as to enhance the signal-to-noise ratio of the superimposed signal; (6) The pseudo code signal output by the local pseudo code generator is mixed with the Doppler frequency shift signal by the same downsampling factor as in step (4), and then FFT transformation is performed and conjugate is taken; (7) performing FFT transformation on each data block after aliasing in step (4), multiplying the result with the result of step (6), performing IFFT transformation and taking the modulus; (8) Perform threshold judgment on the result of step (7), perform inverse aliasing operation on the pseudo code phase basket with peaks exceeding the threshold value, obtain p pseudo code phase values, perform correlation operation on these p pseudo code phase values and the complex signal under the searched Doppler frequency shift, and the pseudo code phase point corresponding to the maximum correlation value is the pseudo code phase that is accurately captured; if no peak exceeding the threshold value appears, reset the Doppler frequency shift signal of step (6) to the next search frequency point, and repeat steps (6) and (7); In step (3), the two-dimensional matrix after data block division is L horizontal blocks and N vertical blocks. Each horizontal block has N data representing the sampled data within a pseudo code period, and each vertical block has L data. The sampling interval between data is one pseudo code period. For the i-th vertical block, ignoring the noise term, the mathematical expression s(·) of each point is: In the formula, C k is the pseudo-random noise code of satellite k, which is a periodic function; D k is the navigation message of satellite k, and is a constant when the length of the read data does not exceed the bit jump period; f k is the carrier frequency of satellite k. Affected by Doppler frequency shift, the carrier frequency of each satellite is different. s is the sampling period; is the initial carrier phase, j is the imaginary unit; In step (4), after aliasing each horizontal block of data, the mathematical expression for the i-th vertical block becomes: In the formula, the downsampling factor is Take an integer; B = N / p, which is the number of data baskets after aliasing; a is the data selection factor, a = 0, 1, ..., p-1; the sampling frequency of the vertical block is f p , that is, the pseudo code frequency, whose value is the inverse of the pseudo code period. If the carrier frequency is divided into f p The integer multiple and remainder of f k =Ff p +Δf k (3) Where F is an integer, 0<Δf k <f p , then the sampling point of the i-th vertical block is expressed as: In step (5), the result of performing FFT transformation on the i-th vertical block is: In the formula, the data of the i-th vertical block is replaced by Y(i,m), ω m is the refined angular frequency, ω m =2πmf p / L, m=0,1,…,L-1, Δω is Δf k The corresponding angular frequency, Δω=2πΔf k , at this time the data of the mth horizontal block is: At the sampling time of the mth horizontal block data, A(m) is a common item that is independent of the sampling time, and its modulus is expressed as: When Δω=ω m When , formula (7) takes the maximum value L, the data can be accumulated to increase the signal-to-noise ratio by 10lgL decibels.