Signal processing method, system, equipment and medium

Abstract

The invention relates to the technical field of signal processing based on the Beidou technology, in particular to a signal processing method, system, equipment and medium, which comprises the following steps: capturing a received satellite navigation signal, and adaptively switching to use different capturing algorithms according to a real-time evaluation result of signal intensity so as to capture in strong and weak signal environments; and tracking the captured signal, and generating an unambiguous discrimination function by constructing and synthesizing a cross-correlation function of a local reference signal and a received signal according to a BOC modulation mode adopted by the signal so as to drive a tracking loop and eliminate false locking caused by multimodality. The method has the beneficial effects that the false locking phenomenon is fundamentally eliminated, and high precision and reliability of final deformation monitoring data are guaranteed.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology based on BeiDou technology, and in particular to a signal processing method, system, device and medium. Background Technology

[0002] With the increasing demands for safety monitoring of small hydropower stations in my country, high-precision deformation monitoring technology based on the dedicated Beidou navigation system has become a key technical means for early warning of dam slope instability and prevention of dam failure risks because it can achieve all-weather, real-time millimeter-level displacement monitoring.

[0003] However, in practical applications, especially in the complex mountainous environments where small hydropower stations are located, existing signal processing technologies face a dual challenge: On the one hand, during the signal acquisition stage, satellite signals are severely attenuated by mountains and vegetation, resulting in a large dynamic range of signal strength. Existing single acquisition algorithms struggle to balance processing speed under strong signals with acquisition sensitivity under weak signals, leading to low acquisition success rate and poor reliability in harsh signal environments. On the other hand, during the signal tracking stage, the BOC modulation signal used in existing technologies to improve anti-interference and ranging accuracy has multiple side peaks in its autocorrelation function. This causes traditional delay-locked loops to easily lock onto these side peaks during tracking, resulting in significant ranging errors and affecting the accuracy and reliability of the final deformation monitoring data. Summary of the Invention

[0004] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a signal processing method, including capturing received satellite navigation signals, wherein different capture algorithms are adaptively switched based on real-time evaluation results of signal strength, so as to capture signals in both strong and weak signal environments. The acquired signal is tracked. For the BOC modulation method used in the signal, an unambiguous discrimination function is generated by constructing and synthesizing the cross-correlation function of the local reference signal and the received signal to drive the tracking loop and eliminate false locking caused by multi-peaks.

[0005] In a preferred embodiment of the signal processing method of the present invention, different acquisition algorithms are adaptively switched based on the real-time evaluation results of the signal strength, including: Determine the frequency of the signal and calculate its intensity; Compare the signal strength with a preset threshold; When the signal strength is higher than the preset threshold, the first type of acquisition algorithm is used for processing; When the signal strength is lower than or equal to the preset threshold, the second type of acquisition algorithm is used for processing.

[0006] In a preferred embodiment of the signal processing method of the present invention, the method includes: constructing and synthesizing a cross-correlation function between a local reference signal and a received signal, including... Generate at least two predefined local reference waveforms; Calculate the cross-correlation function between the received BOC modulated signal and each local reference waveform; The obtained cross-correlation functions are mathematically synthesized to generate a pseudo-correlation function with only a single main peak, which serves as an unambiguous discrimination function.

[0007] As a preferred embodiment of the signal processing method of the present invention, at least two predefined local reference waveforms are designed and generated based on the spread spectrum chip waveforms of the original BOC signal by setting specific pulse widths and weighting factors.

[0008] In a preferred embodiment of the signal processing method of the present invention, the obtained multiple cross-correlation functions are mathematically synthesized, including performing a combination operation based on the square values ​​of the multiple cross-correlation functions to generate a pseudo-correlation function with only a single main peak.

[0009] As a preferred embodiment of the signal processing method of the present invention, the first type of acquisition algorithm is a PMF-FFT algorithm based on partially matched filtering and fast Fourier transform.

[0010] As a preferred embodiment of the signal processing method of the present invention, the second type of acquisition algorithm is the double-block zero-filling DBZP algorithm.

[0011] In a second aspect, the present invention provides a signal processing system, comprising: an acquisition module for acquiring received satellite navigation signals, wherein different acquisition algorithms are adaptively switched according to the real-time evaluation results of the signal strength, so as to be able to acquire signals in both strong and weak signal environments; The tracking module is used to track the received signal after it has been captured. Specifically, for the BOC modulation method used in the signal, a non-ambiguous discrimination function is generated by constructing and synthesizing the cross-correlation function between the local reference signal and the received signal to drive the tracking loop and eliminate false locking caused by multi-peaks.

[0012] Thirdly, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described above.

[0013] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described above.

[0014] Compared with existing technologies, the beneficial effects of this invention are as follows: In terms of acquisition sensitivity, the proposed PMF-FFT and DBZP adaptive switching mechanism can dynamically select the optimal processing strategy based on the real-time power detection value of the RF front end. When the signal is attenuated to a weak signal mode due to mountain obstruction, the dual-block energy accumulation and zero-padding processing mechanism of the DBZP algorithm can achieve a processing gain of several dB to 10 dB compared with the traditional B1I signal acquisition, significantly expanding the availability boundary of the monitoring system in complex obstruction environments. In terms of real-time parallel processing capability, the large-scale FFT / IFFT operations inherent in the PMF-FFT and DBZP algorithms are parallelized and reconstructed using the GPU many-core architecture, giving full play to the advantage of reducing the algorithm complexity from O(N²) to O(NlogN). Moreover, the shorter the coherence integration time, the more significant the parallel acceleration effect. Both of these together ensure the engineering requirements of continuity, reliability and high precision for small hydropower deformation monitoring. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating a signal processing method.

[0017] Figure 2 This is a block diagram of the adaptive decision-making switching module.

[0018] Figure 3 This is a block diagram of the signal pre-detection unit.

[0019] Figure 4 This is a block diagram of the phase-locked loop signal detection module.

[0020] Figure 5 This is a schematic diagram of the PMF-FFT algorithm.

[0021] Figure 6 This is a schematic diagram of the BDS transmission link.

[0022] Figure 7 This explains the principle of the DBZP algorithm.

[0023] Figure 8 The waveforms are for the CBOC(6,1,1 / 11) signal and two local reference waveforms.

[0024] Figure 9 This is a novel CBOC signal DLL structure based on a pseudo-correlation function. Detailed Implementation

[0025] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0026] Example 1, referring to Figure 1 This is the first embodiment of the present invention, which provides a signal processing method, including: S100: Acquires received satellite navigation signals, and adaptively switches between different acquisition algorithms based on real-time assessment of signal strength to acquire signals in both strong and weak signal environments. S200: Tracks the acquired signal. For the BOC modulation method used in the signal, a non-ambiguous discrimination function is generated by constructing and synthesizing the cross-correlation function of the local reference signal and the received signal to drive the tracking loop and eliminate false locking caused by multi-peaks.

[0027] Therefore, to address the challenges of signal acquisition and tracking in complex environments for small hydropower deformation monitoring, this method, through steps S100-S200, intelligently switches between different acquisition algorithms by real-time evaluation of channel conditions. This ensures rapid and reliable initial acquisition under various signal conditions, from strong to weak, laying the foundation for subsequent processing. By synthesizing a pseudo-correlation function, the inherent multi-peak nature of the BOC signal is actively eliminated, forcing the tracking loop to stably lock onto a single main peak. This fundamentally eliminates false locking and ensures the high accuracy and reliability of the final deformation monitoring data. These two steps complement each other, jointly solving the core signal processing challenges faced by the BeiDou monitoring system in complex mountainous environments.

[0028] Example 2, refer to Figures 1-9 As an embodiment of the present invention, a signal processing method is provided based on the above embodiment.

[0029] In this embodiment of the application, step S100 involves capturing the received satellite navigation signal. This includes adaptively switching between different capture algorithms based on real-time assessments of signal strength, to ensure capture in both strong and weak signal environments. This includes the following steps A1-A4: like Figure 2As shown, an adaptive judgment and switching module is used to achieve adaptive signal strength determination and seamless switching between PMF-FFT acquisition and DBZP acquisition, in order to cope with the channel problems caused by the complex and ever-changing spectrum environment of small hydropower stations. It should be noted that the device is located between the RF front-end and the baseband signal processing unit, enabling adaptive judgment and switching of the acquisition module.

[0030] Furthermore, the adaptive decision-making switching module consists of a signal pre-detection unit, cascaded threshold decision units 1~N, and an adaptive acquisition unit. The signal pre-detection unit rapidly and in real-time detects the RF signal SIF(n) output from the RF front-end; when the signal pre-detection unit detects N signal frequencies f1~f... N When (N≥1), f1~f N Thresholds are sequentially assigned to threshold decision units 1 through N; each threshold decision unit determines thresholds according to f1 through f... N The signal power is determined, and the acquisition unit is then notified to switch between PMF-FFT acquisition and DBZP acquisition.

[0031] A1: Determine the frequency of the signal and calculate its strength.

[0032] like Figure 3 As shown, the signal pre-detection unit consists of a discrete FFT signal spectrum analysis module and parallel phase-locked loop signal detection modules 1~N. The input interface of the signal pre-detection unit includes the intermediate frequency signal SIF(n) output from the RF front-end and the signal tracking Doppler f... doppler The output interface is for accurately detecting signal frequencies f1~f N .

[0033] It should be noted that the FFT signal spectrum analysis module is used to achieve fast coarse detection of SIF(n). The detection frequency range is set to [f0-∆f, f0+∆f], where f0 is the standard center frequency of each RNSS signal, and ∆f is set to the detection frequency range > 8MHz. The FFT signal spectrum analysis module outputs the coarse detection signal frequencies Sf1~Sf N Precise detection is performed on phase-locked loop signal detection modules 1~N.

[0034] like Figure 4 As shown, the input interface of the phase-locked loop signal detection module is the coarse detection signal frequency Sf. N The output interface is for accurately detecting the signal frequency f. N The phase-locked loop (PLL) signal detection module uses a typical digital PLL structure to detect the signal, with Sf... NUsing the base frequency, local quadrature signals uos(n) and uoc(n) are generated by looking up sine and cosine tables using the carrier NCO. uos(n) and uoc(n) are then mixed with the intermediate frequency signal SIF(n) to obtain down-converted signals i(n) and q(n), respectively. These signals are then integrated and cleared to increase the signal gain, resulting in I(n) and Q(n), which are fed into the loop lock indicator. If the loop lock indicator detects a lock, it outputs a precise detection signal frequency f. N The signal is sent to the threshold determination subunit. If it fails to lock, the detection process exits. Simultaneously, I(n) and Q(n) are sent to the discriminator to obtain the discrimination result φe(n). After being filtered by the loop filter, the result is sent back to the carrier NCO to achieve continuous and stable tracking of the signal.

[0035] Preferably, this step achieves rapid and accurate positioning of the signal frequency through a cascaded scheme of FFT coarse detection + PLL fine detection. Only by accurately knowing the signal frequency can its power (intensity) be accurately calculated at that frequency point, avoiding inaccurate intensity measurement caused by frequency deviation.

[0036] Furthermore, the threshold monitoring unit (a cascaded threshold determination unit 1~N and an adaptive capture threshold determination unit) measures the signal frequency f. N Envelope calculation yields the signal strength P. N。

[0037] In an optional implementation, determining the signal frequency and calculating its intensity in step A1 can also be achieved through a blind estimation method based on parallel energy accumulation in the Doppler frequency domain. Specifically, N parallel Doppler frequency shift compensation channels are preset in the baseband processing unit, with a frequency interval of 500Hz covering a range of ±10kHz. The intermediate frequency digital signal is simultaneously fed into each channel for carrier stripping, and then coherently integrated with the local pseudocode for 1ms. The magnitude of the integration result for each channel is extracted as the energy observation value. An energy-frequency curve is fitted using cubic spline interpolation, and the frequency corresponding to the peak point of the curve is the estimated Doppler frequency shift value f. N The peak energy, after being normalized by AGC gain, is converted into the received signal strength P. N .

[0038] In another optional implementation, determining the signal frequency and calculating its intensity in step A1 can also be achieved through autocorrelation domain analysis based on the statistical distribution of short-time correlation peaks. Specifically, the received intermediate frequency signal is divided into sliding segments with a 1ms window. Each segment undergoes partial correlation with the local pseudocode at three preset candidate frequency points. The amplitudes of the correlation peaks in each segment are extracted to form a statistical sample set. The ratio of the mean to the standard deviation of the sample set is calculated as the signal-to-noise ratio estimate. When this ratio exceeds a preset threshold T... N The presence of a signal is determined at the specified time, and the candidate frequency with the highest peak frequency is used as f. NOutput.

[0039] A2: Compare the signal strength with a preset threshold.

[0040] It should be noted that the preset threshold T N It is set based on the system's definition of strong and weak signals, hardware performance (such as noise figure), and application requirements (such as minimum acceptable sensitivity), so it is not limited here.

[0041] A3: When the signal strength is higher than the preset threshold, the first type of acquisition algorithm is used for processing.

[0042] It should be noted that the first type of acquisition algorithm is the PMF-FFT algorithm based on partially matched filtering and fast Fourier transform. This algorithm can significantly expand the Doppler frequency range of the acquisition search. Compared with the matched filter algorithm, the PMF-FFT algorithm has fewer fast Fourier transform operations, reducing design difficulty and hardware resource consumption. Specifically, the algorithm first performs time-domain signal segmentation matching, then performs FFT transform on the output of the partially matched filter and takes the modulus value, observing the spectral peaks in the frequency domain and making a decision. The spectral peaks of the PMF-FFT search algorithm may suffer from scallop loss. The method to solve the scallop loss problem is to window or zero-padding the data.

[0043] like Figure 5 As shown, the mixer's inputs are an intermediate frequency (IF) digital signal and an IF carrier signal, respectively. The IF digital signal is mixed to obtain a complex baseband signal. The partially matched filter has a length of L, and its inputs are the complex baseband signal and the local ranging code signal. In implementation, the partially matched filter can be equivalent to partial correlation, so the output is the correlation integral result of L complex baseband signal sample points and local ranging code signal sample points. The order of the partially matched filter is n, and the product of the partially matched filter length and the order is the number of sample points corresponding to one period of ranging code. The outputs of the n partially matched filters are used as the inputs of the FFT transform. The output of the FFT transform is the coherent integral result. If the peak value of the coherent integral result is greater than the decision threshold, the acquisition is determined to be successful and the code phase and Doppler frequency are output; otherwise, the process proceeds to the next ranging code search unit.

[0044] Understandably, because the PMF-FFT algorithm uses serial search in the time domain, the time delay and computational complexity of the PMF-FFT algorithm increase linearly with the length of the ranging code. Therefore, in modern signal systems, the PMF-FFT algorithm is not suitable for direct acquisition of long code signals.

[0045] Ideally, under good signal conditions, the system can complete the initial synchronization with extremely high efficiency, quickly creating conditions for subsequent tracking steps.

[0046] A4: When the signal strength is lower than or equal to the preset threshold, the second type of capture algorithm is used for processing.

[0047] It is understandable that the BDS signal transmission process is affected by link loss, thermal noise, and Doppler frequency offset, which changes the power of the received signal and thus affects signal reception.

[0048] like Figure 6 As shown in the figure, the propagation process of a BDS signal can be divided into three parts: signal transmission, spatial transmission, and signal reception. It can be seen from the figure that the BDS signal experiences spatial transmission loss during transmission, which causes the received signal strength to change relative to the transmitted signal. Therefore, the impact of link transmission loss must be considered when designing the transmit power and antenna gain. The following is the signal transmission equation: In the formula: PR is the antenna's received power, PT is the antenna's transmitted power, GT is the antenna's transmitted gain, d is the transmission distance, GR is the antenna's received gain, λ is the carrier wavelength, LA is the atmospheric loss, and M is the polarization attenuation.

[0049] That is, in mountainous areas, the signal strength may be much lower than the receiver's normal reception threshold, so a high-sensitivity algorithm (such as DBZP) is necessary to deal with it.

[0050] Furthermore, the thermal noise of the receiver is typically generated by thermal motion, and its corresponding noise power is as follows: In the formula: k is the Boltzmann constant 1.38×10-23J / K; T is the ambient temperature, typically 290K; Bn is the receiver noise width.

[0051] In other words, weak signals are not only difficult to capture, but also difficult to track stably after capture, because noise will seriously interfere with the processing.

[0052] It should be noted that the second type of acquisition algorithm is the dual-block zero-padding DBZP algorithm, which performs a dual-block operation on the received spread spectrum signal (to ensure the continuity of acquisition) and zero-padding on the local pseudocode signal (to match its length with the signal block length, thus enabling direct cyclic convolution operations using FFT), cleverly utilizing the slider concept. The correlation integral calculation between the received signal and the local signal borrows the idea of ​​the PCS algorithm, using the FFT+IFFT method to obtain the correlation results of the partially matched filter, such as... Figure 7As shown, the received baseband signal and the locally generated spreading code are first divided into blocks, that is, the signal blocks are appropriately overlapped (double blocks), and the local code blocks are padded with zeros to meet the requirements of FFT operation. Further, for each pair of signal blocks and the zero-padded local code blocks, a PCS-like operation is performed: FFT is performed on both, one of the spectra is conjugated, a dot product is performed in the frequency domain, and an IFFT is performed on the dot product result to obtain the partial correlation result between the signal block and the local code block. Finally, all the partial correlation results are combined in a "slider" manner to obtain a complete correlation result plane (including code phase and Doppler frequency). Then, peak detection and acquisition decision are performed (the correlation peak is searched on this complete search plane. If the peak exceeds the threshold, the acquisition is successful, and the corresponding code phase and Doppler frequency values ​​are output).

[0053] Ideally, this step ensures that the system still has reliable signal acquisition capabilities even in harsh environments where signals are severely blocked or attenuated, expanding the applicability of the entire monitoring system and enabling the acquisition of core targets in both strong and weak signal environments.

[0054] In an optional implementation, the acquisition of the received satellite navigation signal in step S100 can also be achieved through an adaptive parameter adjustment method based on the positioning solution quality feedback. That is, after the initial acquisition and locking is completed, the PDOP value and positioning variance of the RTK positioning solution are continuously monitored. When the PDOP value exceeds 3.0 or the positioning variance is greater than 0.05m², it is determined that the current signal quality has deteriorated. The coherent integration time of the acquisition module is automatically extended from 1ms to 10ms and the number of non-coherent accumulations is increased from 1 to 5. At the same time, the frequency search step is reduced from 500Hz to 250Hz to improve the acquisition sensitivity. The parameters are gradually rolled back until the positioning index recovers to the normal threshold, so as to achieve a dynamic balance between acquisition sensitivity and real-time performance.

[0055] In another optional implementation, the acquisition of the received satellite navigation signal in step S100 can also be achieved through a signal enhancement method based on multi-antenna spatial filtering and digital beamforming. Specifically, a three-element circular antenna array is deployed at the monitoring station, with the spacing between each antenna element being half a wavelength. First, digital beamforming is performed on the three intermediate frequency signals. The Capon adaptive algorithm is used to form a gain beam in the direction of the BeiDou satellite and a null in the direction of the obstruction, thereby improving the signal-to-noise ratio of the array output signal by 6-8 dB. Then, the enhanced signal is sent to the standard PCS acquisition engine for code phase-Doppler two-dimensional search. This method decouples spatial filtering from the acquisition algorithm, and can achieve stable acquisition of weak signals in mountainous and obstructed environments without modifying the acquisition algorithm itself. When a single antenna fails, it automatically switches to dual-antenna diversity mode to ensure monitoring continuity.

[0056] In this embodiment of the application, step S200 involves tracking the captured signal. Specifically, for the BOC modulation scheme used in the signal, an unambiguous discrimination function is generated by constructing and synthesizing the cross-correlation function between the local reference signal and the received signal to drive the tracking loop and eliminate false locking caused by multi-peak behavior. This includes the following steps B1-B3: Understandably, BOC modulation can solve the problem of signal spectrum separation and has a larger root mean square bandwidth compared to BPSK signals, which can improve signal anti-interference and tracking accuracy.

[0057] B1: Generate at least two predefined local reference waveforms.

[0058] It should be noted that at least two predefined local reference waveforms are designed and generated based on the spread spectrum chip waveforms of the original BOC signal by setting specific pulse widths and weighting factors.

[0059] For example, taking the CBOC(6,1,1 / 11) signal as an example, it is itself a weighted sum of BOC(1,1) and BOC(6,1), where the amplitude of BOC(1,1) is... The amplitude of BOC(6,1) is .like Figure 8 As shown, the CBOC signal is a complex four-level waveform. It can also be seen from the figure that in addition to the main peak, there are two side peaks in the autocorrelation function of the CBOC signal. This will lead to loss of lock or false lock during the tracking process, affecting the tracking accuracy.

[0060] Specifically, Tc = Ts / M. Therefore, the spreading code symbol can also be represented as: In the formula: Tc represents the spreading chip period; Ts represents the subcarrier half-period; M represents the oversampling factor; Indicates rounding up; , This represents the magnitude weighting factor, where, , .

[0061] Furthermore, the two locally designed reference waveforms are as follows: Figure 8 As shown, its definition is as follows: In the formula: n = 1, 2; This represents the j-th chip of the PRN code, whose spreading code period is T. c ,d nThe signal waveforms designed for two local channels can be represented as follows: In the formula: L is the pulse width of the local design code.

[0062] Preferably, this special design allows the two waveforms to produce specific, complementary responses when cross-correlated with the received BOC signal. Although their respective cross-correlation functions with the BOC signal may still have multiple peaks, their peak-valley characteristics are misaligned and complementary.

[0063] In an optional implementation, the generation of the predefined local reference waveform in step B1 can also be achieved through a subcarrier component orthogonal separation and independent mapping method. That is, for the two subcarrier components BOC(1,1) and BOC(6,1) in the CBOC(6,1,1 / 11) signal, their power distribution relationship is completely decoupled, and the first local waveform is generated as a pure BOC(1,1) four-level waveform. The second channel generates a pure BOC(6,1) four-level waveform. After the two are independently cross-correlated with the received signal, the optimal weighted least squares synthesis is used in the subsequent B3 step instead of direct difference. The gain of each correlator is maximized through component decoupling. An additional 2-3dB processing margin can be obtained in the weak signal environment in mountainous areas. Moreover, when one subcarrier is distorted by multipath interference, the stability of the other waveform tracking can still be maintained.

[0064] In another alternative implementation, the generation of the predefined local reference waveform in step B1 can also be achieved through correlation peak splitting elimination based on complex domain phase rotation, i.e., extending the traditional real domain local waveform to a complex domain representation to generate a single-channel complex waveform. , where the phase function By using IQ quadrature modulation, the autocorrelation function of the received BOC signal presents a spiral trajectory on the complex plane, with the side peaks corresponding to a 90-degree phase shift while the main peak remains in phase at 0 degrees. The subsequent phase detector directly extracts the real part of the complex correlation function as the unambiguous discrimination function.

[0065] B2: Calculate the cross-correlation function between the received BOC modulated signal and each local reference waveform.

[0066] It should be noted that, in order to completely eliminate the side peaks of the autocorrelation function of the CBOC signal and obtain unambiguous measurement values, the following is taken: The ASPeCT method is a special case (L=6, β=1). Therefore, the cross-correlation function between the received CBOC signal and the locally constructed reference waveform signal can be expressed as: In the formula: n=1,2 represent the signals designed locally. and T is the coherent integration time. dCBOC represents the CBOC signal vector. By using a reasonably designed local signal spreading code waveform, and considering the characteristics of the two cross-correlation functions in the formula, the pseudo-correlation function without side peaks can be obtained using the two cross-correlation functions derived from this formula: Choosing an appropriate coefficient β can eliminate stable false locking points, but redundant peaks still exist in the ASPeCT correlation function.

[0067] To overcome the problem of redundant peaks still existing in the ASPeCT method, this method designs a novel CBOC signal DLL structure based on a pseudo-correlation function, such as... Figure 9 As shown in the diagram. Inside the receiver, the captured BOC signal is mixed with locally generated quadrature carriers, down-converted to the I and Q branches of the baseband, and two additional correlators are added to each of the I and Q branches. The received signal is cross-correlated with the locally generated waveform at multiple code phase points (such as leading and lagging), and then passed through an integrator and clearer to finally obtain two (or more) sets of cross-correlation functions.

[0068] B3: Mathematically synthesize the multiple cross-correlation functions obtained to generate a pseudo-correlation function with only a single main peak, which serves as an unambiguous discrimination function.

[0069] It should be noted that the mathematical synthesis of the obtained multiple cross-correlation functions includes combining the squares of the multiple cross-correlation functions to generate a pseudo-correlation function with only a single main peak.

[0070] Specifically, the received CBOC signal is multiplied by the local carrier and then down-converted to the baseband I and Q branches. The signals on these two branches are then correlated with the locally designed signal. After passing through an integrator and clearer, the resulting pseudo-correlation function can be expressed as: In the formula: i = E, L represent lead and lag, respectively. Finally, the output of the new DLL phase detector is: In the formula: d represents the lead-lag correlator interval.

[0071] Ideally, during the combination operation (energy difference), the energy of the main peak is synergistically enhanced because it is strong in both functions; while the energy of the side peaks, which are stronger in one function than the other, are mutually canceled and weakened during the combination operation. That is, the side peaks of the new function (pseudo-correlation function) are completely eliminated or suppressed to a level far below that of the main peak, thus presenting a single, sharp main peak.

[0072] In an optional implementation, the tracking of the captured signal in step S200 can also be achieved through a BOC main peak locking method based on decision feedback and carrier phase consistency verification. That is, while using a traditional early and late code tracking loop, a carrier phase change rate monitoring module is added. After the code loop is locked, the variance of the carrier phase difference value of adjacent epochs is continuously calculated. If the variance exceeds a preset threshold, it is determined to be a false lock of the side peak. At this time, the decision unit outputs the reconstructed pulse driving code NCO to perform phase scanning within a range of ±0.5 chip to recapture the main peak. The average phase difference value of 20 consecutive epochs after carrier-assisted code loop locking is used as a reference, and the deviation is compared in real time to maintain the main peak locking.

[0073] In another optional implementation, the tracking of the captured signal in step S200 can also be achieved through an adaptive main peak identification method based on a dual-timescale correlator group. That is, two sets of parallel early and late correlators are configured in each of the I / Q branches. The short integral group has an integration time of 0.5ms for fast response to side peak changes, and the long integral group has an integration time of 5ms for smoothing the main peak energy. The two groups generate their own phase detection errors. By comparing the ratio of the long-term statistical mean of the short integral group to the instantaneous value of the long integral group, when the ratio is less than 0.7, the current tracking point is determined to be a side peak. The code loop bandwidth is automatically switched from 2Hz to 0.5Hz and a reverse correction pulse is injected to force the loop to pull towards the main peak.

[0074] In summary, regarding acquisition sensitivity, the proposed PMF-FFT and DBZP adaptive switching mechanism can dynamically select the optimal processing strategy based on the real-time power detection value of the RF front end. When the signal is attenuated to a weak signal mode due to mountain obstruction, the DBZP algorithm's dual-block energy accumulation and zero-padding processing mechanism can achieve a processing gain improvement of several dB to 10 dB compared to the traditional B1I signal acquisition, significantly expanding the availability boundary of the monitoring system in complex obstruction environments. In terms of real-time parallel processing capability, the large-scale FFT / IFFT operations inherent in the PMF-FFT and DBZP algorithms are parallelized and reconstructed using a GPU many-core architecture, giving full play to the advantage of reducing the algorithm complexity from O(N²) to O(NlogN). Moreover, the shorter the coherence integration time, the more significant the parallel acceleration effect. Together, they ensure the engineering requirements of continuity, reliability, and high accuracy for small hydropower deformation monitoring.

[0075] Example 3 illustrates a signal processing method. It should be noted that the technical solution of this signal processing system and the technical solution of the signal processing method described above belong to the same concept. Details not described in detail in this example can be found in the description of the technical solution of the signal processing method described above.

[0076] This embodiment also provides a signal processing system, including: The acquisition module is used to acquire received satellite navigation signals. Based on the real-time evaluation of signal strength, it adaptively switches between different acquisition algorithms to acquire signals in both strong and weak signal environments. The tracking module is used to track the received signal after it has been captured. Specifically, for the BOC modulation method used in the signal, a non-ambiguous discrimination function is generated by constructing and synthesizing the cross-correlation function between the local reference signal and the received signal to drive the tracking loop and eliminate false locking caused by multi-peaks.

[0077] This embodiment also provides an electronic device suitable for signal processing, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the signal processing method proposed in the above embodiment.

[0078] This embodiment also provides a storage medium on which a computer program is stored, which, when executed by a processor, implements the signal processing method as proposed in the above embodiments.

[0079] The storage medium proposed in this embodiment and the signal processing method proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0080] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0081] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A signal processing method, characterized in that: include, The received satellite navigation signals are acquired, wherein different acquisition algorithms are adaptively switched based on the real-time evaluation results of the signal strength, so that acquisition can be achieved in both strong and weak signal environments; The captured signal is tracked. For the BOC modulation method used in the signal, an unambiguous discrimination function is generated by constructing and synthesizing the cross-correlation function of the local reference signal and the received signal to drive the tracking loop and eliminate false locking caused by multi-peaks.

2. The signal processing method as described in claim 1, characterized in that: The method adaptively switches between different capture algorithms based on the real-time evaluation results of the signal strength. include, Determine the frequency of the signal and calculate its intensity; The signal strength is compared with a preset threshold; When the signal strength is higher than the preset threshold, the first type of acquisition algorithm is used for processing; When the signal strength is lower than or equal to the preset threshold, the second type of capture algorithm is used for processing.

3. The signal processing method as described in claim 1, characterized in that: The construction and synthesis of the cross-correlation function between the local reference signal and the received signal includes, Generate at least two predefined local reference waveforms; Calculate the cross-correlation function between the received BOC modulated signal and each of the local reference waveforms; The obtained cross-correlation functions are mathematically synthesized to generate a pseudo-correlation function with only a single main peak, which serves as the unambiguous discrimination function.

4. The signal processing method as described in claim 3, characterized in that: The at least two predefined local reference waveforms are designed and generated based on the spread spectrum chip waveforms of the original BOC signal by setting specific pulse widths and weighting factors.

5. The signal processing method as described in claim 3, characterized in that: The mathematical synthesis of the obtained multiple cross-correlation functions includes performing a combination operation based on the square values ​​of the multiple cross-correlation functions to generate the pseudo-correlation function with only a single main peak.

6. The signal processing method as described in claim 2, characterized in that: The first type of capture algorithm is the PMF-FFT algorithm based on partially matched filtering and fast Fourier transform.

7. The signal processing method as described in claim 2, characterized in that: The second type of capture algorithm is the double-block zero-filling DBZP algorithm.

8. A signal processing system, employing the method as described in any one of claims 1-7, characterized in that, include: The acquisition module is used to acquire received satellite navigation signals, wherein different acquisition algorithms are adaptively switched based on the real-time evaluation results of the signal strength, so that acquisition can be performed in both strong and weak signal environments; The tracking module is used to track the received signal after it has been captured. Specifically, for the BOC modulation method used on the signal, a non-ambiguous discrimination function is generated by constructing and synthesizing the cross-correlation function between the local reference signal and the received signal to drive the tracking loop and eliminate false locking caused by multi-peaks.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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