Communication and navigation integrated signal receiving and processing method for parasitic low-frequency communication signal
By preprocessing parasitic low-frequency communication signals and combining generalized quadratic cross-correlation time delay estimation with cubic spline interpolation, the problems of time delay estimation accuracy and computational complexity under low signal-to-noise ratio are solved, achieving high-precision time delay estimation and accurate demodulation.
Patent Information
- Application Number
- CN202511499608.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-20
- Publication Date
- 2026-02-27
AI Technical Summary
Under conditions of strong electromagnetic countermeasures and satellite navigation denial, high-precision time delay estimation and accurate demodulation of parasitic low-frequency communication signals are difficult to achieve in low signal-to-noise ratio environments. Existing algorithms suffer from problems such as high computational complexity, poor robustness, and large time delay estimation errors.
A preprocessing scheme involving receiver filtering, envelope detection, and coherent accumulation is adopted to improve the signal-to-noise ratio of the received signal. A coarse delay estimate is obtained by combining a generalized quadratic cross-correlation delay estimation algorithm, and precise detection is performed near the peak of the cross-correlation function through cubic spline interpolation to improve the accuracy of the delay estimation.
High-precision time delay estimation was achieved under low signal-to-noise ratio, with the root mean square error of time delay estimation reduced to the level of 0.1 μs, the bit error rate reduced to 10⁻⁴, and the computational complexity reduced.
Smart Images
Figure CN121578338A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of signal processing technology, and specifically relates to a method for integrated communication and navigation signal reception and processing of parasitic low-frequency communication signals. Background Technology
[0002] Under conditions of strong electromagnetic interference and satellite navigation denial, various satellite navigation terminals cannot function properly. Broadcast resources are abundant, and signals propagated via ground waves offer strong stability, making them an important carrier for land-based navigation systems. By embedding ranging information into broadcast signals, a high-precision, highly reliable, flexible, and low-cost PNT (Positioning and Navigation Tolerance) solution can be provided to ensure the navigation and positioning functions of various platform terminals under satellite navigation denial, achieving reliable long-range positioning even in such conditions.
[0003] Integrated communication and navigation signals that rely on low-frequency communication signals typically transmit over long distances. Therefore, achieving high-precision time delay estimation and accurate demodulation of these integrated signals under low signal-to-noise ratio (SNR) conditions is a critical challenge. The accuracy of time delay estimation directly impacts the final positioning performance; thus, researching high-precision time delay estimation techniques is essential. Currently, commonly used time delay estimation algorithms include adaptive time delay estimation algorithms, subspace time delay estimation algorithms, phase spectrum time delay estimation algorithms, and generalized cross-correlation (GCC) algorithms. Adaptive algorithms can estimate the time delay difference between signals without requiring statistical prior knowledge of the signal and noise, but their convergence speed is slow, requiring iterative optimization to gradually approximate the true time delay, which takes a long adaptation time and is difficult to meet real-time requirements. Subspace algorithms are mostly based on the theory of signal subspace decomposition and can achieve high-resolution time delay estimation, but they require steps such as multipath number pre-estimation, covariance matrix eigenvalue decomposition, and spectral peak search, which significantly increases computational complexity. Phase spectrum analysis directly estimates the time delay through the phase difference in the frequency domain, which has high computational efficiency, but it is sensitive to frequency domain aliasing and noise and has poor robustness. In contrast, the generalized cross-correlation algorithm has become a research hotspot in the field of time delay estimation due to its advantages such as simple principle, low computational cost, strong stability, and wide applicability. By designing different frequency domain weighting functions (such as PHAT and ML), GCC can achieve an effective balance between noise suppression, reverberation environment adaptability, and computational efficiency, and is therefore widely used in real-time systems such as sound source localization and wireless communication.
[0004] Generalized cross-correlation (GCC) time delay estimation methods estimate time delay by calculating the cross-correlation function between signals and detecting its peak position. Depending on the order of the correlation operation, this method can be divided into several forms, including direct cross-correlation, generalized first-order cross-correlation, generalized second cross-correlation (GSCC), and generalized third cross-correlation (GTCC). Its theoretical model is based on the ideal signal assumption, satisfying the orthogonality condition between noise and signal, and between noise particles. Under high signal-to-noise ratio (SNR) conditions, it can obtain accurate time delay estimates. However, in practical applications, reverberation and noise interference can cause the cross-correlation function peak to become less sharp or even produce spurious peaks, leading to significant deviations in time delay estimation. Furthermore, since GCC-type algorithms use Fast Fourier Transform (FFT) to calculate the signal time delay, the resulting time delay interval is affected by the picket fence effect in FFT spectrum calculation, and is therefore calculated as the sampling period. The time delay estimation accuracy is an integer multiple of 10 ... Therefore, the theoretical error of time delay estimation is affected by the sampling frequency. The higher the sampling frequency, the smaller the time delay estimation error. Although increasing the sampling frequency can improve the accuracy of time delay estimation, due to the constraints of hardware cost, computational complexity and system power consumption, the sampling frequency cannot be increased without limitation in actual use of the algorithm. Summary of the Invention
[0005] To overcome the shortcomings of existing technologies, this invention provides an integrated signal receiving and processing method for parasitic low-frequency communication signals. It improves the received signal-to-noise ratio (SNR) through a preprocessing scheme involving receiver filtering, envelope detection, and coherent accumulation. Then, a generalized quadratic cross-correlation delay estimation algorithm is used to obtain a coarse delay estimate, which can provide time synchronization for coherent demodulation of the signal. To further improve the accuracy of the delay estimation algorithm, cubic spline interpolation is used near the peak of the cross-correlation function for quadratic peak detection, improving the accuracy of signal delay estimation while reducing the computational load.
[0006] The technical solution adopted by this invention to solve its technical problem is as follows: Step 1: The expression for the integrated communication and navigation signal with parasitic low-frequency communication signals is:
[0007] in, To modulate a fully hopping MPPSK signal containing navigation message information; It is an audio signal. It is a DC signal, and the audio signal and the DC signal satisfy... This ensures that the signal is not overmodulated and that the envelope detector at the receiving end can correctly demodulate the analog audio signal. Full-jump MPPSK in one symbol period The simplified expression is:
[0008] in, The carrier period; For carrier frequency; This represents the number of carrier flips in a single transition. The ratio of the symbol period to the carrier period; the transmitted data is... number system; The range of values is By adjusting , , The value of is used to obtain different signal bandwidths, transmission rates, and demodulation performance; Step 2: Before being transmitted through the antenna, the integrated conduction and signal transmission signal passes through a tuning circuit to further constrain the signal spectrum. This tuning circuit is equivalent to a bandpass filter. Therefore, the signal received by the receiver is:
[0009] in, It is the signal transmission attenuation factor; For the transmitting bandpass filter; It is a Gaussian white noise signal; For signal transmission delay; Represents a discrete-time index, indicating the first... n One sampling point; It is a function The discrete-time form is a discrete sequence obtained after sampling; Step 3: The receiving end first processes the received integrated communication and conduction signal. Preprocessing is performed, including receiving-end filtering, envelope detection, and coherent accumulation; the signal after coherent accumulation is... Then, coherent demodulation and generalized second-order cross-correlation time delay estimation are performed; Step 4: Obtain a coarse delay estimate using generalized quadratic cross-correlation time delay estimation; Step 4-1: For and sample signal The two time-domain signals obtained by Fast Fourier Transform are converted into frequency-domain signals. and The sample signal is a locally generated, known frame synchronization header portion;
[0010]
[0011] Step 4-2: Calculation self-power spectral density function and the cross-power spectral density function between the two frequency domain signals :
[0012]
[0013] in, express The conjugate function; Step 4-3: Calculate the second-order cross-power spectrum :
[0014] in, express The conjugate function; Step 4-4: Analyze the second cross-power spectrum from Step 5. The cross-correlation function is obtained by performing an inverse Fourier transform. :
[0015] in Indicates the inverse Fourier transform; Represents the entire frequency domain; It is an imaginary number; For frequency; It is a time variable; Steps 4-5: Apply the cross-correlation function obtained in step 6. Peak detection is performed to obtain a coarse delay estimate. Since the generalized cross-correlation delay estimate is an integer multiple of the sampling interval, the theoretical error of the delay estimate is... The range of values is :
[0016] in, Indicates transmission delay. This indicates the sampling rate.
[0017] Step 5: Perform coherent demodulation on the received signal; Coarse value for time delay estimation Time synchronization detection is performed to locate the start position of the navigation message; then, the carrier signal is extracted via a phase-locked loop and the signal is... The signal is multiplied with the carrier signal, then bandpass filtered and detected and decided, and finally the navigation message information is output. Step 6: Select data near the peak point to construct a cubic spline function, perform cubic spline interpolation within the local range, and then perform secondary peak detection to obtain the accurate time delay estimate. ; Set the number of interpolation points to P, and the theoretical range of the absolute value of the error of the interpolated time delay estimate is: .
[0018] Preferably, the receiving end filter removes some noise and out-of-band signals.
[0019] Preferably, the envelope detector outputs an analog audio signal.
[0020] Preferably, the coherent accumulation improves the signal-to-noise ratio of the received signal.
[0021] An electronic device includes a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device performs the above-described integrated communication and navigation signal receiving and processing method.
[0022] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described integrated communication and navigation signal receiving and processing method.
[0023] A chip includes a processor for retrieving and running a computer program from a memory, causing a device equipped with the chip to perform the aforementioned integrated communication and navigation signal receiving and processing method.
[0024] A computer program product includes a computer storage medium storing a computer program, the computer program including instructions executable by at least one processor, which, when executed by the at least one processor, implement the above-described integrated communication and navigation signal receiving and processing method.
[0025] The beneficial effects of this invention are as follows: To address the challenges of high-precision time delay estimation and accurate demodulation of integrated navigation and communication signals under low signal-to-noise ratio (SNR), this invention employs preprocessing including receiver filtering and coherent accumulation. The preprocessed signal is then compared with a local sample signal using generalized quadratic cross-correlation time delay estimation to obtain a coarse time delay estimate, providing accurate time synchronization for coherent demodulation of navigation messages. Subsequently, cubic spline interpolation is performed near the cross-correlation peak, and a precise time delay estimate is obtained through quadratic peak detection, improving time delay estimation accuracy while reducing computational complexity. This invention achieves sub-sampling rate level time delay estimation accuracy, and at low SNR, the root mean square error (RMSE) of time delay estimation can reach [value missing]. The magnitude is so high that the bit error rate can reach [amount]. Magnitude. Attached Figure Description
[0026] Figure 1 This is a diagram of the integrated communication and navigation signal frame structure.
[0027] Figure 2 A flowchart of the integrated signal reception and processing procedure for parasitic low-frequency communication signals.
[0028] Figure 3 This is a time-domain waveform diagram of the received signal after preprocessing (SNR=0 dB) according to an embodiment of the present invention.
[0029] Figure 4 This is a comparison chart of the RMSE (Residual Time Estimate) of different algorithms in embodiments of the present invention.
[0030] Figure 5 This is a graph showing the coherent demodulation bit error rate curves under different signal-to-noise ratios in an embodiment of the present invention.
[0031] Figure 6 This is a comparison diagram of the cross-correlation peak values before and after cubic spline interpolation in an embodiment of the present invention.
[0032] Figure 7 This is a comparison chart of the RMSE (Reset Time Estimate) of different interpolation algorithms in embodiments of the present invention. Detailed Implementation
[0033] The present invention will be further described below with reference to the accompanying drawings and embodiments.
[0034] This invention provides a method for receiving and processing parasitic low-frequency communication signals using an integrated communication and navigation signal. A preprocessing scheme involving receiver filtering, envelope detection, and coherent accumulation is employed to improve the received signal-to-noise ratio. A generalized quadratic cross-correlation delay estimation algorithm is then used to obtain a coarse delay estimate, which can provide time synchronization for coherent demodulation. To further improve the accuracy of the delay estimation algorithm, cubic spline interpolation is used near the peak of the cross-correlation function for quadratic peak detection, improving the accuracy of signal delay estimation while reducing computational complexity.
[0035] A method for receiving and processing integrated communication and navigation signals with parasitic low-frequency communication signals, comprising the following steps: Step 1: The expression for the integrated communication and navigation signal with parasitic low-frequency communication signals is:
[0036] in, To modulate a fully hopping MPPSK signal containing navigation message information; It is an audio signal. The signal is a DC signal, and the audio signal and the DC signal should satisfy the following conditions: This ensures that the signal is not overmodulated, and that the receiver's envelope detection can correctly demodulate the analog audio signal. Full-switching MPPSK operates within one symbol period. The simplified expression is:
[0037] in, The carrier period; For carrier frequency; This represents the number of carrier flips in a single transition. The ratio of the symbol period to the carrier period; the transmitted data is... number system; The range of values is By adjusting , , The value of can be used to obtain different signal bandwidth, transmission rate and demodulation performance.
[0038] Step 2: Before being transmitted through the antenna, the integrated signal undergoes further spectrum constraint via a tuning circuit. This tuning circuit is equivalent to a bandpass filter. Therefore, the signal received by the receiver is:
[0039] in, For signal transmission attenuation factor, For the transmitting bandpass filter, It is a Gaussian white noise signal. This refers to the signal transmission delay.
[0040] Step 3: The receiving end first processes the received integrated communication and conduction signal. Preprocessing is performed, including receiver filtering, envelope detection, and coherent accumulation. Receiver filtering removes some noise and out-of-band signals, envelope detection outputs an analog audio signal, and coherent accumulation improves the signal-to-noise ratio (SNR) of the received signal. The signal after coherent accumulation is... Then, coherent demodulation and generalized second-order cross-correlation time delay estimation are performed.
[0041] Step 4: Obtain a coarse delay estimate using generalized quadratic cross-correlation time delay estimation; Step 4-1: For and sample signal The two time-domain signals obtained by Fast Fourier Transform are converted into frequency-domain signals. and The sample signal is a locally generated, known frame synchronization header portion.
[0042]
[0043]
[0044] Step 4-2: Calculation self-power spectral density function and the cross-power spectral density function between the two frequency domain signals :
[0045]
[0046] Step 4-3: Calculate the second-order cross-power spectrum :
[0047] Step 4-4: Analyze the second cross-power spectrum from Step 5. The cross-correlation function is obtained by performing an inverse Fourier transform. :
[0048] in Indicates the inverse Fourier transform; Represents the entire frequency domain; It is an imaginary number; For frequency; It is a time variable.
[0049] Steps 4-5: Apply the cross-correlation function obtained in step 6. Peak detection is performed to obtain a coarse delay estimate. The coarse time delay estimate obtained can provide accurate time synchronization for coherent demodulation of the signal. Since the generalized cross-correlation time delay estimate is an integer multiple of the sampling interval, the theoretical error of the time delay estimate is... The range of values is :
[0050] Step 5: Perform coherent demodulation on the received signal. The coarse time delay estimate obtained in Step 7 is then used. Time synchronization detection can be performed to locate the start position of the navigation message. Then, the carrier signal is extracted via a phase-locked loop, and the signal... The signal is multiplied with the carrier signal, then bandpass filtered and detected, and finally the navigation message information is output.
[0051] Step 6: After detecting the peak of the quadratic cross-correlation function in Step 7, select data near the peak point to construct a cubic spline function, perform cubic spline interpolation within the local range, and then perform quadratic peak detection to obtain the accurate time delay estimate. This method improves the accuracy of time delay estimation while reducing the computational load. With the number of interpolation points set to P, the theoretical range of the absolute value of the error in the interpolated time delay estimate is:
[0052] Example: Step 1: Before being transmitted through the transmitting antenna, the integrated conduction signal passes through a tuning circuit, which is equivalent to a bandpass filter with a -50dB bandwidth of 500kHz. After passing through this shaping filter, the integrated conduction signal based on full-hopping MPPSK modulation experiences signal distortion at the phase transition, or even has the phase transition erased. Full-hopping MPPSK modulation has three important parameters. M, N, K Value, by increasing K The value can compensate for the influence of the shaping filter on the signal waveform. The full-switching MPPSK modulation parameters are set to... M =64, K =8, N=M×K The center frequency of the signal 1MHz, sampling rate The frequency is 100MHz, and the signal transmission delay is 2000.5 seconds. The signal coherence accumulation count is 10. The integrated signal frame structure diagram of the parasitic low-frequency communication signal is shown below. Figure 1 As shown, the receiving and processing flow is as follows: Figure 2 As shown.
[0053] Step 2: Perform preprocessing on the received signal, including receiver filtering, envelope detection, and coherent accumulation, to obtain the signal. Taking SNR=0 dB as an example, the preprocessed signal time-domain waveform is as follows: Figure 3 As shown. According to Figure 4 and Figure 5 After 10 coherent accumulations, the signal-to-noise ratio can be effectively improved, thereby further enhancing the performance of subsequent coherent demodulation and delay estimation.
[0054] Step 3: Receive the preprocessed signal With sample signal A coarse time delay estimate is obtained by performing generalized quadratic cross-correlation time delay estimation. A Monte Carlo simulation experiment of 1000 runs is conducted at low signal-to-noise ratio, and the simulation results are as follows: Figure 4 As shown, compared with the direct cross-correlation, generalized cross-correlation, and generalized triple cross-correlation time delay estimation algorithms, the generalized quadratic cross-correlation time delay estimation algorithm has the best performance and can provide accurate time synchronization information for coherent demodulation of signals under low signal-to-noise ratio.
[0055] Step 4: After obtaining the time synchronization information in Step 3, locate the start position of the navigation message and synchronize the signal. Coherent demodulation is performed, the signal is multiplied by the recovered carrier signal, then bandpass filtering and detection / determination are applied, finally outputting the navigation message information. The bit error rate curves of the signal at different signal-to-noise ratios are shown in the figure below. Figure 5 As shown.
[0056] Step 5: Perform cubic spline interpolation on the peak value of the cross-correlation function obtained in Step 3, taking 10 sampling points before and after the peak value, with an interpolation interval of 0.1. The local plots of the cross-correlation peaks before and after interpolation are shown below. Figure 6 As shown. Commonly used interpolation algorithms include linear, nearest, next, pchip, cubic, and frequency domain zero-padding. The RMSE (Residual Time Estimate) results of different interpolation algorithms under low signal-to-noise ratio conditions are shown in the figure. Figure 7 As shown, the time delay estimation algorithm optimized by cubic spline interpolation has the best performance and the highest accuracy.
Claims
1. A communication-navigation integrated signal receiving processing method of a parasitic low frequency communication signal, characterized by, Includes the following steps: Step 1: The expression for the integrated communication and navigation signal with parasitic low-frequency communication signals is: in, To modulate a fully hopping MPPSK signal containing navigation message information; It is an audio signal. It is a DC signal, and the audio signal and the DC signal satisfy... This ensures that the signal is not overmodulated and that the envelope detector at the receiving end can correctly demodulate the analog audio signal. Full-jump MPPSK in one symbol period The simplified expression is: in, The carrier period; For carrier frequency; This represents the number of carrier flips in a single transition. The ratio of the symbol period to the carrier period; the transmitted data is... number system; The range of values is By adjusting , , The value of is used to obtain different signal bandwidths, transmission rates, and demodulation performance; Step 2: Before being transmitted through the antenna, the integrated conduction and signal transmission signal passes through a tuning circuit to further constrain the signal spectrum. This tuning circuit is equivalent to a bandpass filter. Therefore, the signal received by the receiver is: in, It is the signal transmission attenuation factor; For the transmitting bandpass filter; It is a Gaussian white noise signal; For signal transmission delay; Represents a discrete-time index, indicating the first... n One sampling point; It is a function The discrete-time form is a discrete sequence obtained after sampling; Step 3: The receiving end first processes the received integrated communication and conduction signal. Preprocessing is performed, including receiving-end filtering, envelope detection, and coherent accumulation; the signal after coherent accumulation is... Then, coherent demodulation and generalized second-order cross-correlation time delay estimation are performed; Step 4: Obtain a coarse delay estimate using generalized quadratic cross-correlation time delay estimation; Step 4-1: For and sample signal The two time-domain signals obtained by Fast Fourier Transform are converted into frequency-domain signals. and The sample signal is a locally generated, known frame synchronization header portion; Step 4-2: Calculation self-power spectral density function and the cross-power spectral density function between the two frequency domain signals : in, express The conjugate function; Step 4-3: Calculate the second-order cross-power spectrum : in, express The conjugate function; Step 4-4: Analyze the second cross-power spectrum from Step 5. The cross-correlation function is obtained by performing an inverse Fourier transform. : in Indicates the inverse Fourier transform; Represents the entire frequency domain; It is an imaginary number; For frequency; It is a time variable; Steps 4-5: Apply the cross-correlation function obtained in step 6. Peak detection is performed to obtain a coarse delay estimate. Since the generalized cross-correlation delay estimate is an integer multiple of the sampling interval, the theoretical error of the delay estimate is... The range of values is : in, Indicates transmission delay. Indicates the sampling rate; Step 5: Perform coherent demodulation on the received signal; Coarse value for time delay estimation Time synchronization detection is performed to locate the start position of the navigation message; then, the carrier signal is extracted via a phase-locked loop and the signal is... The signal is multiplied with the carrier signal, then bandpass filtered and detected and decided, and finally the navigation message information is output. Step 6: Select data near the peak point to construct a cubic spline function, perform cubic spline interpolation within the local range, and then perform secondary peak detection to obtain the accurate time delay estimate. ; Set the number of interpolation points to P, and the theoretical range of the absolute value of the error of the interpolated time delay estimate is: 。 2. The method for integrated communication and navigation signal reception and processing of parasitic low-frequency communication signals according to claim 1, characterized in that, The receiving end filter removes some noise and out-of-band signals.
3. The integrated communication and navigation signal receiving and processing method for parasitic low-frequency communication signals according to claim 1, characterized in that, The envelope detector outputs an analog audio signal.
4. The method for integrated communication and navigation signal reception and processing of parasitic low-frequency communication signals according to claim 1, characterized in that, The coherent accumulation improves the signal-to-noise ratio of the received signal.
5. An electronic device, characterized in that, include: Processor and memory; The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to cause the electronic device to perform the method as described in any one of claims 1 to 4.
6. 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 method as described in any one of claims 1 to 4.
7. A chip, characterized in that, include: A processor for retrieving and running a computer program from memory, causing a device on which the chip is mounted to perform the method as described in any one of claims 1 to 4.
8. A computer program product, characterized in that, The computer program product includes a computer storage medium storing a computer program, the computer program including instructions executable by at least one processor, which, when executed by the at least one processor, implement the method as described in any one of claims 1 to 4.