A low-complexity, high-precision GNSS high-dynamic signal frequency estimation method and system

Abstract

The present invention relates to a low-complexity, high-precision GNSS high-dynamic signal frequency estimation method and system. The method comprises: modeling a post-correlation signal to obtain a post-correlation signal; performing adjacent differential processing on the post-correlation signal and then integrating it to obtain a nearest-neighbor differential coherent signal; performing multi-dimensional differential accumulation on the nearest-neighbor differential coherent signal and estimating the Doppler change rate of the signal obtained by the multi-dimensional differential accumulation; calculating a differential signal based on the post-correlation signal and integrating it, then performing addition / subtraction processing to obtain a data bit symbol and an accumulated amount corresponding to each flip position; performing maximum position determination on the accumulated amount to obtain the actual data flip position; removing bits from the post-correlation signal to obtain a signal to be processed, performing coherent integration processing on the signal to be processed, and then performing Doppler frequency estimation on the signal after the coherent integration processing. The present invention realizes low-complexity and high-precision frequency parameter estimation in a high-dynamic environment.

Description

Technical Field

[0001] The present invention belongs to the field of communication technology, and in particular relates to a low-complexity, high-precision, high-dynamic GNSS signal frequency estimation method and system. Background Art

[0002] Satellite signal capture technology is an important component in GNSS software radio receivers. In this process, the code phase and Doppler frequency need to be estimated. Many software receivers use a coarse-fine capture method, that is, the signal is first coarsely captured, the code phase and frequency are roughly estimated, and then the frequency is finely captured. When performing fine frequency capture, the signal is modeled as a post-correlation signal. At this time, in a high-dynamic environment, the peak is affected not only by Doppler but also by the frequency change rate. Therefore, when performing fine frequency estimation of a high-dynamic post-correlation signal, it is necessary to estimate the two frequency parameters of Doppler and Doppler change rate, and the estimation will be affected by bit flipping. The more popular algorithm is the BASIC method, such as Figure 4 As shown in FIG, two-step FFT is used to estimate the frequency parameters, but the frequency estimation accuracy needs to be further improved.

[0003] Therefore, it is necessary to conduct in-depth research on the problem of high-precision estimation of frequency parameters of high-dynamic post-correlation signals and propose a high-precision and low-complexity Doppler and Doppler change rate estimation method. Summary of the Invention

[0004] The purpose of the present invention is to improve the frequency estimation accuracy with low complexity. In the case of high dynamic data bit flipping, a low-complexity, high-precision GNSS high-dynamic signal frequency estimation method and system are proposed.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A low-complexity, high-precision GNSS high-dynamic signal frequency estimation method comprises the following steps:

[0007] S1. Modeling the post-correlation signal in a high dynamic environment to obtain the post-correlation signal;

[0008] S2, performing adjacent differential processing on the post-correlation signal, and then integrating it to obtain the nearest neighbor differential coherent signal;

[0009] S3. performing multidimensional differential accumulation on the neighboring differential coherent signals, and estimating the Doppler change rate of the signals obtained by the multidimensional differential accumulation to obtain an estimated Doppler change rate;

[0010] S4. Calculate a differential signal based on the post-correlation signal and integrate it, then perform addition / subtraction processing to obtain a data bit symbol and an accumulated amount corresponding to each flip position;

[0011] S5. Determine the maximum position of the accumulated amount to obtain the actual data flip position;

[0012] S6. Remove bits from the post-correlation signal to obtain a signal to be processed, perform coherent integration processing on the signal to be processed, and then perform Doppler frequency estimation on the signal after the coherent integration processing to obtain an estimated Doppler frequency.

[0013] As a preferred solution, in step S1, the post-correlation signal is:

[0014]

[0015] Among them, A represents the signal amplitude, n represents the sampling point, b n Represents the data bit symbol of the nth sampling point, j is the imaginary unit, T s represents the integration time of the rough Doppler frequency estimation, f0 represents the error between the rough Doppler frequency estimation of the GNSS intermediate frequency received signal and the actual Doppler frequency, and α represents the Doppler change rate.

[0016] As a preferred solution, in step S2, adjacent difference processing is performed on the post-correlation signal to obtain:

[0017]

[0018] in,

[0019] Assume n = k1N b ,...,(k1+1)N b -1,b n b n+1 =1, for d r (n) is integrated to obtain the nearest neighbor differential coherent signal:

[0020]

[0021] Where k1=0,...,K a -1, K a Indicates the number of points for Doppler rate of change estimation, N b represents the data bit period, and k1 represents the k1th data bit symbol period.

[0022] As a preferred solution, in step S3, D r (k1) Perform multi-dimensional differential accumulation to obtain signal A i :

[0023]

[0024] where i = 1, .., K a ;

[0025] The signal A obtained by multi-dimensional differential accumulation i Perform Doppler rate of change estimation, including:

[0026] For signal A i Perform adjacent difference accumulation to determine the variable:

[0027]

[0028] Get the estimated Doppler rate of change

[0029] As a preferred solution, in step S4, the differential signal calculated based on the post-correlation signal is:

[0030]

[0031] Where i1=0,1,...,N b -1, α1=α-α e ;

[0032] right Integrating, we get:

[0033]

[0034] in, K represents signal length;

[0035] Then perform the following addition / subtraction processing:

[0036]

[0037] Get the data bit symbol corresponding to each flip position i1 and accumulation

[0038] in,

[0039] As a preferred solution, in step S5,

[0040] Accumulation Make maximum position judgment:

[0041]

[0042] Among them, i0 represents the actual data flip position.

[0043] As a preferred solution, the estimated differential data bits are obtained according to i0 Assuming that the data bit symbol of the zeroth sampling point is 1, that is, b0=1, the estimated data bit symbol of the nth sampling point b is obtained. ne .

[0044] As a preferred solution, in step S6, bits are removed from the post-correlation signal to obtain a signal to be processed:

[0045]

[0046] After that, coherent integration processing is performed to obtain the signal:

[0047]

[0048] Among them, k f =0,...,K f -1, K f Indicates the number of points for Doppler frequency estimation; N f represents the coherent integration time; f h It indicates that the remaining Doppler value range after re-coarse capture is divided into several possible value points, h=1,...,H, H is the subscript of the possible value point;

[0049] For each f h Corresponding Perform Doppler frequency estimation, including:

[0050] right Perform multi-dimensional differential accumulation to obtain the signal

[0051]

[0052] Where l = 1, .., K f ;

[0053] Signal Perform adjacent difference accumulation to determine the variable:

[0054]

[0055] according to The estimated Doppler frequency is:

[0056]

[0057] That is, the maximum value corresponds to the estimated Doppler frequency

[0058] The present invention further provides a low-complexity, high-precision, high-dynamic GNSS signal frequency estimation system, which applies the low-complexity, high-precision, high-dynamic GNSS signal frequency estimation method described in any of the above solutions. The low-complexity, high-precision, high-dynamic GNSS signal frequency estimation system comprises:

[0059] A modeling module, used for modeling the post-correlation signal in a high dynamic environment to obtain the post-correlation signal;

[0060] An adjacent differential processing module, used for performing adjacent differential processing on the post-correlation signal;

[0061] An integration module, used to integrate the signals after adjacent differential processing to obtain a nearest neighbor differential coherent signal;

[0062] A multi-dimensional differential accumulation module, used for performing multi-dimensional differential accumulation on neighbor differential coherent signals;

[0063] A Doppler change rate estimation module is used to estimate the Doppler change rate of the signal obtained by multi-dimensional differential accumulation to obtain an estimated Doppler change rate;

[0064] a calculation module, configured to calculate a differential signal based on the post-correlation signal;

[0065] The integration module is further used to integrate the differential signal;

[0066] An addition / subtraction processing module is used to perform addition / subtraction processing on the differential signal after integration to obtain the data bit symbol and accumulation amount corresponding to each flip position;

[0067] The judgment module is used to judge the maximum position of the accumulated amount and obtain the actual data flip position;

[0068] a bit removal module, configured to remove bits from the post-correlation signal to obtain a signal to be processed;

[0069] A coherent integration processing module, used for performing coherent integration processing on the signal to be processed;

[0070] The Doppler frequency estimation module is used to perform Doppler frequency estimation on the signal after coherent integration processing to obtain an estimated Doppler frequency.

[0071] Compared with the prior art, the present invention has the following beneficial effects:

[0072] The present invention uses neighbor differentials to remove the mutual influence of bit symbols, Doppler and Doppler change rate in Doppler change rate estimation, performs high-precision frequency estimation on neighbor differential signals, then removes the influence of Doppler change rate and uses the difference of adjacent data bit signals to remove the influence of Doppler on bit flipping, and directly estimates the bit symbols; in Doppler estimation, coherent accumulation is used to improve the signal-to-noise ratio, and then Doppler is estimated with high precision; low complexity is used to achieve high-precision frequency parameter estimation in a high dynamic environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 Flowchart of a low-complexity, high-precision, high-dynamic GNSS signal frequency estimation method according to an embodiment of the present invention;

[0074] Figure 2 Comparison of the amount of computation required for the existing BASIC method and the low-complexity, high-precision GNSS high-dynamic signal frequency estimation method according to an embodiment of the present invention; (a) Doppler rate estimation accuracy comparison, (b) Doppler rate detection method calculation complex multiplication comparison, (c) bit flip detection probability comparison;

[0075] Figure 3 Comparison of the complex multiplication computational effort of the existing BASIC method and the low-complexity, high-precision GNSS high-dynamic signal frequency estimation method according to an embodiment of the present invention; (a) Doppler estimation accuracy comparison, (b) Doppler detection method complex multiplication computational effort comparison;

[0076] Figure 4 For the existing BASIC method. DETAILED DESCRIPTION

[0077] To more clearly illustrate the embodiments of the present invention, specific embodiments of the present invention will be described below with reference to the accompanying drawings. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings and other embodiments can be obtained based on these drawings without inventive efforts.

[0078] like Figure 1 As shown, the low-complexity, high-precision, high-dynamic GNSS signal frequency estimation method according to an embodiment of the present invention includes the following steps:

[0079] S1. In a high dynamic environment, the post-correlation signal is modeled as:

[0080]

[0081] Where A represents the signal amplitude, b n Indicates the data bit symbol (referred to as data bit), T srepresents the integration time during coarse capture, n represents the sampling point, f0 represents the error between the rough estimation of Doppler frequency and the actual Doppler frequency, α represents the Doppler change rate, and j is an imaginary unit, the square of which is negative one.

[0082] Perform adjacent difference processing on the post-correlation signal:

[0083]

[0084] in,

[0085] Assume n = k1N b ,...,(k1+1)N b -1,b n b n+1 =1, for d r (n) is integrated to obtain the nearest neighbor differential coherent signal:

[0086]

[0087] Where k1=0,...,K a -1, K a Indicates the number of points for Doppler rate of change estimation, N b represents the data bit period, and k1 represents the k1th data bit symbol period.

[0088] To D r (k) Perform multi-dimensional differential accumulation to obtain signal A i :

[0089]

[0090] Where i = 1, .., K a .

[0091] Then the signal A obtained by multi-dimensional differential accumulation is i The Doppler rate of change is estimated as follows:

[0092] First, for signal A i Perform further adjacent difference accumulation to determine the variable:

[0093]

[0094] Second, an estimate of the Doppler rate of change can be obtained

[0095] The above is the Doppler change rate estimation process.

[0096] Then, calculate the differential signal:

[0097]

[0098] Where i1=0,1,...,N b -1, α1=α-α e , N b Indicates the data bit period.

[0099] right To perform integration:

[0100]

[0101] in, K represents signal length.

[0102] Then perform the following addition / subtraction process to obtain the data bit symbol corresponding to each flip position i1: and accumulation

[0103]

[0104] in,

[0105] Then the accumulation Make maximum position judgment:

[0106]

[0107] Among them, i0 represents the actual data flip position; according to i0, we can get represents the estimated differential data bits;

[0108] According to the assumption that the data bit symbol of the zeroth sampling point is 1, that is, b0=1, the estimated data bit symbol of the nth sampling point b can be obtained. ne .

[0109] S2. Estimation of Doppler frequency

[0110] The signal to be processed can be written as

[0111]

[0112] Perform coherent integration on:

[0113]

[0114] Among them, k f =0,...,K f -1, K f Indicates the number of points for Doppler frequency estimation; N f represents the coherent integration time; fh It indicates that the remaining Doppler value range after re-coarse capture is divided into several possible value points, h=1,...,H, H is the subscript of the possible value point;

[0115] For each f h Corresponding Perform Doppler frequency estimation based on complex angle as follows:

[0116] First, yes Perform multi-dimensional differential accumulation of signals

[0117]

[0118] Where l = 1, .., K f ;

[0119] Signal Perform further adjacent difference accumulation to determine the variable:

[0120]

[0121] Second, it can be concluded that

[0122] The above is the Doppler estimation process, and the final estimated Doppler frequency is:

[0123]

[0124] R f (n) is processed as above, and the maximum value corresponds to the estimated Doppler frequency

[0125] In summary, the estimated Doppler frequency change rate α can be obtained e , bit flip position i0, and estimated Doppler frequency f 0e .

[0126] Table 1 compares the amount of complex multiplication calculations based on the existing BASIC method (BASIC for short) and the above method according to the embodiment of the present invention (the proposed method for short):

[0127] Table 1

[0128]

[0129] Among them, N F Represents the length of the post-correlation signal, N b represents the data bit period, N cf =1 / (T s △ f ),△ αIndicates the accuracy of the estimated Doppler rate of change, △ f Indicates the accuracy of estimated Doppler, N F0 is the number of Doppler searches (i.e., Doppler coarse acquisition).

[0130] like Figure 2 The figure shows a comparison of the Doppler rate estimation accuracy, computational complexity (number of multiplications), and bit flip detection probability between the prior art method and the high dynamic frequency estimation method of the present invention. α =40Hz / s 2 It can be seen from (a) that when SNR=10dB, the method proposed by the present invention (K a =20) and BASIC(K a =10) has similar estimation accuracy, but from (b) we can see that the method proposed in this invention has much smaller number of times of multiplication than BASIC, and from (c) we can see that the proposed method (K a =20) has a slightly higher detection probability than BASIC (K a =10) of the detection probability.

[0131] In summary, since the complexity (number of multiplications) of the method in the embodiment of the present invention is much lower than that of BASIC, it is possible to improve K a Improve estimation accuracy and detection probability, and achieve low-complexity and high-precision Doppler change rate estimation.

[0132] like Figure 3 The figure shows a comparison of the Doppler estimation accuracy and the amount of calculation (number of complex multiplications) between the prior art method and the high dynamic frequency estimation method of the present invention. f =0.02Hz. In (a), at a high signal-to-noise ratio such as 10dB, the method proposed by the present invention (K a =20) and BASIC(K a =10) have similar estimation accuracy, but from (b), we can find that the proposed method (K a =20) than BASIC(K a =10) is much smaller. Therefore, by increasing K a , achieving low-complexity and high-precision Doppler estimation.

[0133] Among them, the Doppler value is randomly selected in [-300,300] Hz, and the Doppler change rate is [-500,500] Hz / s 2 The signal is the post-correlation signal model of GPS L1 CA code in GNSS system, so N b =20ms,T s =1ms, and the number of Monte Carlo simulations is 2000, which can greatly reduce the amount of calculation.

[0134] Based on the low-complexity, high-precision GNSS high-dynamic signal frequency estimation method according to an embodiment of the present invention, the embodiment of the present invention also provides a low-complexity, high-precision, high-dynamic signal frequency estimation system, including:

[0135] A modeling module, used for modeling the post-correlation signal in a high dynamic environment to obtain the post-correlation signal;

[0136] An adjacent differential processing module, used for performing adjacent differential processing on the post-correlation signal;

[0137] An integration module, used to integrate the signals after adjacent differential processing to obtain a nearest neighbor differential coherent signal;

[0138] A multi-dimensional differential accumulation module, used for performing multi-dimensional differential accumulation on neighbor differential coherent signals;

[0139] A Doppler change rate estimation module is used to estimate the Doppler change rate of the signal obtained by multi-dimensional differential accumulation to obtain an estimated Doppler change rate;

[0140] a calculation module, configured to calculate a differential signal based on the post-correlation signal;

[0141] The integration module is further used to integrate the differential signal;

[0142] An addition / subtraction processing module is used to perform addition / subtraction processing on the differential signal after integration to obtain the data bit symbol and accumulation amount corresponding to each flip position;

[0143] The judgment module is used to judge the maximum position of the accumulated amount and obtain the actual data flip position;

[0144] a bit removal module, configured to remove bits from the post-correlation signal to obtain a signal to be processed;

[0145] A coherent integration processing module, used for performing coherent integration processing on the signal to be processed;

[0146] A Doppler frequency estimation module is used to perform Doppler frequency estimation on the signal after coherent integration processing to obtain an estimated Doppler frequency;

[0147] The specific execution process of all the above modules can be referred to the detailed description in the method steps and will not be repeated here.

[0148] The above description is only a detailed description of the preferred embodiments and principles of the present invention. For ordinary technicians in this field, based on the ideas provided by the present invention, there may be changes in the specific implementation methods, and these changes should also be considered as the scope of protection of the present invention.

Claims

1. A low-complexity, high-precision GNSS high-dynamic signal frequency estimation method, characterized in that: The following steps are involved: S1. Modeling the post-correlation signal in a high dynamic environment to obtain the post-correlation signal; S2, performing adjacent differential processing on the post-correlation signal, and then integrating it to obtain the nearest neighbor differential coherent signal; S3. performing multidimensional differential accumulation on the neighboring differential coherent signals, and estimating the Doppler change rate of the signals obtained by the multidimensional differential accumulation to obtain an estimated Doppler change rate; S4. Calculate a differential signal based on the post-correlation signal and integrate it, then perform addition / subtraction processing to obtain a data bit symbol and an accumulated amount corresponding to each flip position; S5. Determine the maximum position of the accumulated amount to obtain the actual data flip position; S6. Remove bits from the post-correlation signal to obtain a signal to be processed, perform coherent integration processing on the signal to be processed, and then perform Doppler frequency estimation on the signal after the coherent integration processing to obtain an estimated Doppler frequency.

2. A low-complexity, high-precision, high-dynamic GNSS signal frequency estimation method according to claim 1, characterized in that: In step S1, the post-correlation signal is: Among them, A represents the signal amplitude, n represents the sampling point, b n Represents the data bit symbol of the nth sampling point, j is the imaginary unit, T s represents the integration time of the rough Doppler frequency estimation, f0 represents the error between the rough Doppler frequency estimation of the GNSS intermediate frequency received signal and the actual Doppler frequency, and α represents the Doppler change rate.

3. A low-complexity, high-precision, high-dynamic GNSS signal frequency estimation method according to claim 2, characterized in that: In step S2, adjacent difference processing is performed on the post-correlation signal to obtain: in, Assume n = k1N b ,...,(k1+1)N b -1,b n b n+1 =1, for d r (n) is integrated to obtain the nearest neighbor differential coherent signal: Where k1=0,...,K a -1, K a Indicates the number of points for Doppler rate of change estimation, N b represents the data bit period, and k1 represents the k1th data bit symbol period.

4. A low-complexity, high-precision, high-dynamic GNSS signal frequency estimation method according to claim 3, characterized in that: In step S3, D r (k1) Perform multi-dimensional differential accumulation to obtain signal A i : where i = 1, .., K a ; The signal A obtained by multi-dimensional differential accumulation i Perform Doppler rate of change estimation, including: For signal A i Perform adjacent difference accumulation to determine the variable: Get the estimated Doppler rate of change 5. A low-complexity, high-precision, high-dynamic GNSS signal frequency estimation method according to claim 4, characterized in that: In step S4, the differential signal obtained by calculating based on the post-correlation signal is: Among them,i1=0,1,...,N b -1, α1=α-α e ; right Integrating, we get: in, K represents signal length; Then perform the following addition / subtraction processing: Get the data bit symbol corresponding to each flip position i1 and accumulation in, 6. A low-complexity, high-precision, high-dynamic GNSS signal frequency estimation method according to claim 5, characterized in that: In the step S5, Accumulation Make maximum position judgment: Among them, i0 represents the actual data flip position.

7. A low-complexity, high-precision, high-dynamic GNSS signal frequency estimation method according to claim 6, characterized in that: Get the estimated differential data bits based on i0 Assuming that the data bit symbol of the zeroth sampling point is 1, that is, b0=1, the estimated data bit symbol of the nth sampling point b is obtained. ne .

8. The low-complexity, high-precision, high-dynamic GNSS signal frequency estimation method according to claim 7, characterized in that: In step S6, bits are removed from the post-correlation signal to obtain a signal to be processed: After that, the coherent integration process is performed to obtain the signal: Among them, k f =0,...,K f -1, K f Indicates the number of points for Doppler frequency estimation; N f represents the coherent integration time; f h It indicates that the remaining Doppler value range after re-coarse capture is divided into several possible value points, h=1,...,H, H is the subscript of the possible value point; For each f h Corresponding Perform Doppler frequency estimation, including: right Perform multi-dimensional differential accumulation to obtain the signal Where l = 1, .., K f ; Signal Perform adjacent difference accumulation to determine the variable: according to The estimated Doppler frequency is: That is, the maximum value corresponds to the estimated Doppler frequency 9. A low-complexity, high-precision, high-dynamic GNSS signal frequency estimation system, applying the low-complexity, high-precision, high-dynamic GNSS signal frequency estimation method according to any one of claims 1 to 8, characterized in that: The low-complexity, high-precision, high-dynamic GNSS signal frequency estimation system comprises: A modeling module, used for modeling the post-correlation signal in a high dynamic environment to obtain the post-correlation signal; An adjacent differential processing module, used for performing adjacent differential processing on the post-correlation signal; An integration module, used to integrate the signals after adjacent differential processing to obtain a nearest neighbor differential coherent signal; A multi-dimensional differential accumulation module, used for performing multi-dimensional differential accumulation on neighbor differential coherent signals; A Doppler change rate estimation module is used to estimate the Doppler change rate of the signal obtained by multi-dimensional differential accumulation to obtain an estimated Doppler change rate; a calculation module, configured to calculate a differential signal based on the post-correlation signal; The integration module is further used to integrate the differential signal; An addition / subtraction processing module is used to perform addition / subtraction processing on the differential signal after integration to obtain the data bit symbol and accumulation amount corresponding to each flip position; The judgment module is used to judge the maximum position of the accumulated amount and obtain the actual data flip position; a bit removal module, configured to remove bits from the post-correlation signal to obtain a signal to be processed; A coherent integration processing module, used for performing coherent integration processing on the signal to be processed; The Doppler frequency estimation module is used to perform Doppler frequency estimation on the signal after coherent integration processing to obtain an estimated Doppler frequency.

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