Spread spectrum signal acquisition method and system suitable for high dynamic low carrier-to-noise ratio scenarios

Abstract

The application provides a spread spectrum signal acquisition method and system suitable for high dynamic low carrier-to-noise ratio scenes. The method comprises the following steps: S1, preprocessing a spread spectrum signal to obtain a digital baseband signal; S2, segmenting and parallel correlating the digital baseband signal and a local pseudo-random sequence to output a plurality of partial correlation results; S3, performing N-point fast Fourier transform on the plurality of partial correlation results; S4, non-coherent accumulation of frequency domain energy spectrum output by continuous multiple N-point fast Fourier transforms to obtain an accumulated energy spectrum; S5, extracting a main maximum modulus value, a secondary maximum modulus value and an average modulus value of all energy spectrum points in the accumulated energy spectrum; S6, judging whether the following conditions are simultaneously satisfied: a ratio of the main maximum modulus value to the average modulus value is greater than a first threshold value, and a ratio of the main maximum modulus value to the secondary maximum modulus value is greater than a second threshold value; and S7, if the conditions are not satisfied, adjusting a phase of the local pseudo-random sequence and returning to step S2.

Description

Technical Field

[0001] This application mainly relates to the field of deep space communication technology, and in particular to a spread spectrum signal acquisition method and system suitable for high dynamic and low carrier-to-noise ratio scenarios. Background Technology

[0002] In deep space exploration missions, the distance between spacecraft and ground stations can reach hundreds of thousands to hundreds of millions of kilometers, resulting in significant signal attenuation and extremely low carrier-to-noise ratios. Simultaneously, the high-speed relative motion between spacecraft and ground generates Doppler frequency shifts as high as ±450 kHz and Doppler variation rates as high as 5 kHz / s. In this extreme environment of high dynamics and low carrier-to-noise ratio, spread spectrum communication, with its advantages of high processing gain, interference resistance, and ranging accuracy, is widely used for deep space tracking and control communications.

[0003] Spread spectrum communication is a communication method that expands the bandwidth of the original information signal to a level far exceeding its minimum required bandwidth. At the transmitting end, the original data is modulated with a high-rate pseudo-random sequence, broadening the signal spectrum. At the receiving end, the same pseudo-random sequence is used for despreading, restoring the wideband signal to a narrowband signal. Despreading requires that the pseudo-random sequence generated locally at the receiver be synchronized with the pseudo-random sequence in the received signal in both code phase and carrier frequency. This process is divided into acquisition and tracking. Acquisition, which requires estimating the code phase start position and the approximate carrier Doppler frequency within a short time, is a crucial step in spread spectrum receivers. Therefore, designing a rapid acquisition method suitable for the high-dynamic, low-carrier-to-noise ratio environment of deep space is a key technology supporting deep space exploration missions.

[0004] The Partially Matched Filter-Fast Fourier Transform (PMF-FFT) method segments long pseudocodes, performs partial matched filtering, and then performs FFT on the segmented results. This allows for simultaneous searching of code phase and Doppler frequency, balancing acquisition time and resource consumption to some extent. However, existing PMF-FFT methods still have the following shortcomings in extremely low carrier-to-noise ratio (CNR) and high dynamic environments: Under extremely low CNR conditions, the signal-to-noise ratio after a single PMF-FFT processing is still very low, resulting in a high false alarm rate for direct peak detection and difficulty in reliably acquiring signals; Existing methods have a single decision threshold, which is prone to false acquisition. Existing methods typically use only a fixed threshold or a simple peak-to-noise mean ratio threshold for decision-making, which cannot effectively suppress two types of false acquisition simultaneously: false alarms caused by noise spikes and multi-peak false locking caused by signal side peaks.

[0005] Therefore, how to achieve fast, low false alarm, and high-sensitivity spread spectrum signal acquisition in the high-dynamic, extremely low carrier-to-noise ratio deep space environment is a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0006] The technical problem to be solved by this application is to provide a spread spectrum signal acquisition method and system suitable for high dynamic and low carrier-to-noise ratio scenarios, and to solve the problems of insufficient sensitivity and easy misjudgment of the single threshold in the existing PMF-FFT method under extremely low carrier-to-noise ratio.

[0007] To address the aforementioned technical problems, this application provides a spread spectrum signal acquisition method suitable for high dynamic range, low carrier-to-noise ratio scenarios, comprising: Step S1: Receive the spread spectrum signal and sample it at a preset sampling rate to obtain the digital baseband signal; Step S2: Using a partially matched filter array composed of multiple partially matched filters, the digital baseband signal and the local pseudo-random sequence are segmented and correlated in parallel to output multiple partial correlation results; Step S3: Perform an N-point Fast Fourier Transform on the multi-path partial correlation results to obtain the frequency domain energy spectrum, where N is a power of 2; Step S4: Perform non-coherent accumulation on the frequency domain energy spectrum of the N-point Fast Fourier Transform output multiple times to obtain the accumulated energy spectrum; Step S5: Extract the principal maximum modulus, the secondary maximum modulus, and the average modulus of all energy spectrum points from the accumulated energy spectrum. Step S6: Determine whether the following conditions are met simultaneously: the ratio of the principal maximum modulus to the average modulus is greater than a first threshold, and the ratio of the principal maximum modulus to the secondary maximum modulus is greater than a second threshold; Step S7: If the conditions are met, the acquisition is considered successful, and the current code phase and Doppler frequency estimate are output; if the conditions are not met, the phase of the local pseudo-random sequence is adjusted, and the process returns to step S2 until the acquisition is successful or the maximum number of attempts is reached.

[0008] Optionally, the partially matched filter array includes P partially matched filters, each with a length of L, and satisfies P×L = M, where M is the total length of the local pseudo-random sequence.

[0009] Optionally, the length L of the partially matched filter can range from 11 to 31.

[0010] Optionally, before performing the N-point Fast Fourier Transform, the method further includes: zero-padding the multi-path partial correlation results to N points to refine the frequency resolution and reduce the scallop loss caused by the deviation of the true Doppler frequency from the discrete frequency points.

[0011] Optionally, the N-point Fourier transform is performed using a processing clock with a frequency higher than the sampling rate.

[0012] Optionally, in step S7, multiple parallel capture channels are used, each capture channel corresponding to a different start code phase of the local pseudo-random sequence, and each capture channel executes steps S2 to S6 in parallel; when any capture channel successfully captures, all capture channels are stopped and the overall capture is determined to be successful.

[0013] Optionally, the plurality of parallel capture channels include a first capture channel and a second capture channel, wherein the first capture channel scans from code phase 0 of the local pseudo-random sequence and the second capture channel scans from code phase 512.

[0014] Optionally, the decision in step S6 adopts the Tang detection strategy, including: in each dwell stage, the first threshold and the second threshold are used for decision making, and the first threshold and / or the second threshold have different values ​​in different dwell stages.

[0015] Optionally, the first threshold is 24 and the second threshold is 1.25.

[0016] To address the aforementioned technical problems, this application provides a spread spectrum signal acquisition system suitable for high dynamic range, low carrier-to-noise ratio scenarios, comprising: The sampling module is used to receive the spread spectrum signal and sample it at a preset sampling rate to obtain the digital baseband signal; The partially matched filter array module, composed of multiple partially matched filters, is used to perform segmented parallel correlation between the digital baseband signal and the local pseudo-random sequence, and output multiple partial correlation results. The Fourier transform module is used to perform an N-point Fourier transform on the multi-path partial correlation results to obtain the frequency domain energy spectrum, where N is a power of 2. The noncoherent accumulation module, connected to the Fourier transform module, is used to noncoherently accumulate the frequency domain energy spectrum of the N-point fast Fourier transform output multiple times to obtain the accumulated energy spectrum. The peak detection module, connected to the non-coherent accumulation module, is used to extract the principal maximum modulus, the secondary maximum modulus, and the average modulus value of all energy spectral points from the accumulated energy spectrum. A dual threshold decision module is used to determine whether the following conditions are met simultaneously: the ratio of the principal maximum modulus to the average modulus is greater than a first threshold, and the ratio of the principal maximum modulus to the secondary maximum modulus is greater than a second threshold. The control and phase scanning module is connected to the partially matched filter array module and the dual threshold decision module, respectively. When the decision is not satisfied, the phase of the local pseudo-random sequence is adjusted and the partially matched filter array module is re-triggered until the acquisition is successful or the maximum number of attempts is reached. When the decision is satisfied, the current code phase and Doppler frequency estimate are output.

[0017] Optionally, the partially matched filter array module includes P partially matched filters, each with a length of L, and satisfies P×L = M, where M is the total length of the local pseudo-random sequence.

[0018] Optionally, the Fourier transform module further includes a zero-padding unit, which is used to zero-padding the multi-path partial correlation results to N points before performing the N-point fast Fourier transform, so as to refine the frequency resolution and reduce the scallop loss caused by the deviation of the true Doppler frequency from the discrete frequency points.

[0019] Optionally, the control and phase scanning module is configured to: employ multiple parallel acquisition channels, each acquisition channel corresponding to a different start code phase of the local pseudo-random sequence, and each acquisition channel triggers the partially matched filter array module, Fourier transform module, non-coherent accumulation module, peak detection module, and dual threshold decision module in parallel; when any acquisition channel successfully acquires, all acquisition channels are stopped and the overall acquisition is determined to be successful.

[0020] Compared with the prior art, this application has the following advantages: This application presents a spread spectrum signal acquisition method and system suitable for high-dynamic, low-carrier-to-noise-ratio scenarios. By forcing non-coherent accumulation to sum multiple frequency-domain energy spectra, it solves the problem of insufficient sensitivity in a single PMF-FFT. Employing dual threshold decision (simultaneous satisfaction of the main maxima / mean ratio and the main maxima / secondary maxima ratio), it significantly reduces the false alarm probability and effectively suppresses false locking caused by pseudo-code sidepeaks and FFT sidelobes. This application achieves a balance between second-level acquisition, high detection probability, and low false alarm rate, making it particularly suitable for resource-constrained, high-dynamic deep space environments such as those of DRO satellites. Attached Figure Description

[0021] The accompanying drawings are included to provide a further understanding of this application. They are incorporated into and constitute a part of this application. The drawings illustrate embodiments of this application and, together with this specification, serve to explain the principles of this application.

[0022] Figure 1 This is a schematic diagram of a spread spectrum signal acquisition system applicable to high dynamic low carrier-to-noise ratio scenarios according to an embodiment of this application.

[0023] Figure 2 This is a flowchart of a spread spectrum signal acquisition method applicable to high dynamic low carrier-to-noise ratio scenarios according to an embodiment of this application.

[0024] Figure 3 This is a graph showing the effect of different matched filter lengths on gain according to an embodiment of this application. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0026] To better understand the technical solution of this application, the following terms are first defined and explained: Spread spectrum signal: refers to a communication signal whose bandwidth is much larger than the minimum necessary bandwidth of the transmitted information signal, and is usually generated by modulation of the original information with a high-speed pseudo-random sequence. The spread spectrum signal in this application is a weak signal received by a deep space telemetry and control transponder, with a carrier-to-noise ratio as low as -30dBHz.

[0027] A local pseudo-random sequence (PN sequence) is a reference sequence generated internally by the receiver and synchronized with the spreading code sequence used by the transmitter. This sequence has good autocorrelation and cross-correlation properties and is used to perform correlation operations with the received signal to achieve despreading and acquisition of the spread spectrum signal.

[0028] A partially matched filter (PMF) divides a full-length local pseudo-random sequence into several consecutive, non-overlapping short segments, with each segment corresponding to a shorter PMF. Each PMF performs a correlation operation between its corresponding segment chip sequence and the received signal, outputting a partial correlation result. Multiple PMFs operate in parallel, forming a partially matched filter array.

[0029] The Fast Fourier Transform (FFT) is an efficient and fast algorithm for the Discrete Fourier Transform. Its core function is to transform a finite-length discrete time-domain signal sequence into a frequency-domain sequence, thereby revealing the frequency components of the signal and its amplitude and phase information.

[0030] Non-coherent integration refers to the process of accumulating the energy spectra of signals over multiple consecutive periods (such as the magnitude or squared magnitude of the FFT output). Unlike coherent integration, non-coherent integration does not require continuous signal phase and is simple to implement.

[0031] Scallop Loss refers to the phenomenon where, when the frequency of the real signal falls exactly at the midpoint between two Discrete Fourier Transform (FFT) frequency points, the signal energy is dispersed across multiple adjacent frequency points, causing the amplitude of the dominant frequency (the point with the highest energy) to decrease relative to the peak value of the real signal. Since the spectrum output by the FFT is a discrete "fence," it's like looking at a continuously changing spectrum through a fence. When the signal peak is "hidden" between two fences, the energy we see appears smaller. This energy loss is called scallop loss, resembling the undulations of a scallop's edge.

[0032] Tang detection is a multi-resident sequence detection strategy. Its core idea is to distinguish between real signals and noise false alarms by multiple consecutive verifications with different thresholds, rather than relying on a single decision.

[0033] Figure 1 This is a schematic diagram of a spread spectrum signal acquisition system suitable for high dynamic range, low carrier-to-noise ratio scenarios, according to an embodiment of this application. Figure 1 As shown, the spread spectrum signal acquisition system includes: Sampling module 1 receives the spread spectrum signal and samples it at a preset sampling rate to obtain a digital baseband signal. The digital baseband signal exists as I-channel and Q-channel quadrature components, preserving the amplitude and phase information of the original signal. Spread spectrum acquisition requires utilizing the phase of the pseudocode and the Doppler frequency offset of the carrier; the digital baseband signal can completely characterize this information. The original spread spectrum signal is usually located at radio frequency, which is very high, making direct processing difficult and costly. Through down-conversion and sampling, the received spread spectrum signal is transformed into a baseband I / Q signal suitable for digital processing, providing the correct signal format for subsequent code phase and Doppler joint search.

[0034] Partially matched filter array module 2 consists of P partially matched filters, denoted as PMF1, PMF2, ..., PMF. P-1 PMF P Each PMF has a length of L, and P × L = M, where M is the total length of the local pseudo-random sequence. Partially matched filter array module 2 is used to perform segmented parallel correlation between the digital baseband signal and the local pseudo-random sequence, outputting multiple partial correlation results. In practice, the system uses segmented processing: PMF1 processes the first L chips of the received sequence, PMF2 processes the next L chips, and so on, until the entire local pseudo-random sequence is traversed.

[0035] Fourier transform module 3 is used to perform an N-point Fourier transform on the multi-path partial correlation results to obtain the frequency domain energy spectrum, where N is a power of 2.

[0036] Noncoherent accumulation module 4, connected to the Fourier transform module, is used to noncoherently accumulate the frequency domain energy spectrum of the N-point fast Fourier transform output multiple times to obtain the accumulated energy spectrum. Peak detection module 5, connected to noncoherent accumulation module, is used to extract the principal maximum modulus, the secondary maximum modulus, and the average modulus of all energy spectral points from the accumulated energy spectrum. The dual threshold decision module 6 is used to determine whether the following conditions are met simultaneously: the ratio of the principal maximum modulus to the average modulus is greater than the first threshold, and the ratio of the principal maximum modulus to the secondary maximum modulus is greater than the second threshold. The control and phase scanning module 7 is connected to the partially matched filter array module and the dual threshold decision module, respectively. It is used to adjust the phase of the local pseudo-random sequence and re-trigger the partially matched filter array module when the decision is not satisfied, until the acquisition is successful or the maximum number of attempts is reached; and to output the current code phase and Doppler frequency estimate when the decision is satisfied.

[0037] This application also provides a spread spectrum signal acquisition method suitable for high dynamic range, low carrier-to-noise ratio scenarios. For example... Figure 2 As shown, spread spectrum signal acquisition methods suitable for high dynamic range and low carrier-to-noise ratio scenarios include: Step S1: Receive the spread spectrum signal and sample it at a preset sampling rate to obtain the digital baseband signal.

[0038] The original spread spectrum signal is usually located at radio frequency (RF), which is very high and difficult and costly to process directly. The received RF spread spectrum signal is amplified with low noise, down-converted to zero intermediate frequency (IF), and then processed at a sampling rate of... Analog-to-digital conversion is performed to obtain digital baseband signals (I / Q channels), providing the correct signal format for subsequent code phase and Doppler joint search.

[0039] Step S2: Using a partially matched filter array consisting of multiple partially matched filters, the digital baseband signal and the local pseudo-random sequence are segmented and correlated in parallel, and the multi-channel partial correlation results are output.

[0040] Optionally, the partially matched filter array contains P partially matched filters, each with a length of L, and satisfies P×L = M, where M is the total length of the local pseudo-random sequence.

[0041] Taking a local pseudo-random sequence with a total length M = 1023 chips (corresponding to a 1ms period) as an example, the number of partially matched filters P = 93, each with a length L = 11 chips, satisfying 93 × 11 = 1023. This embodiment uses a single acquisition channel as an example, dividing the received signal into consecutive 20ms time blocks (each block containing 20 pseudo-random sequence periods). Within each 20ms block, the local pseudo-random sequence is correlated with the received signal in segments in parallel. Specifically: The local pseudo-random sequence (1023 chips long) is divided into 93 non-overlapping segments, each 11 chips long. Each segment corresponds to a partially matched filter (PMF). Each PMF multiplies and accumulates its 11 chips with the corresponding 11 chips in the received signal, with the accumulation process spanning a 20ms coherent integration. Since the pseudo-random sequence is the same within each period, the 20ms coherent accumulation is equivalent to adding the partial correlation results of 20 periods, thus achieving a 20-fold processing gain. The 93 PMFs operate in parallel, outputting 93 partial correlation results after a 20ms coherent integration time. Each partial correlation result is a complex number containing I / Q components.

[0042] Optionally, before proceeding to step S3, the method further includes the step of zero-padding the multi-path partial correlation results to N points to refine the frequency resolution and reduce the scallop loss caused by the deviation of the true Doppler frequency from the discrete frequency points.

[0043] Let P be the number of effective correlation results output by the partially matched filter array. If we directly perform an FFT on these P points, the frequency resolution will be... In deep-space high-dynamic scenarios, this results in a wide interval between each frequency search unit, much larger than the actual Doppler change step size of the signal. Coarse resolution can cause the true Doppler frequency to likely fall between two discrete frequency points, leading to energy dispersion. This application includes a zero-padding operation before performing an N-point Fast Fourier Transform on the multi-path partial correlation results. (NP) zeros are padded after the P data points, expanding the total data length to N points, where N is a power of 2. Zero-padding does not increase the effective information of the signal, but it refines the frequency resolution by increasing the number of FFT points, thereby reducing the scallop loss caused by the true Doppler frequency deviating from the discrete frequency points. When P=93 and N=8192, 8099 zeros are padded after 93 effective data points, and then an 8192-point FFT is performed using an 80MHz clock. Compared to performing FFT directly on 93 points, the frequency resolution is improved from about 110kHz to about 1.25kHz, and the scallop loss is reduced from 3.9dB to about 0.5dB, which significantly improves the detection sensitivity under extremely low carrier-to-noise ratio.

[0044] Step S3: Perform an N-point Fast Fourier Transform on the multi-path partial correlation results to obtain the frequency domain energy spectrum, where N is a power of 2.

[0045] The P-path correlation results constitute a time-domain sequence of length P, where each value reflects the correlation (including amplitude and phase information) between the local pseudo-random sequence and the received signal in the corresponding segment. An N-point Fast Fourier Transform (FFT) is performed on this time-domain sequence, where N is a power of 2 (e.g., 8192). Typically, N is greater than P, so (NP) zeros are padded to the end of the original P data points before the transform. The FFT transforms the time-domain sequence to the frequency domain, outputting N complex numbers, each corresponding to a discrete frequency point. The modulus (or squared modulus) of the FFT output complex numbers is typically taken to obtain N real numbers, forming the frequency-domain energy spectrum.

[0046] Because Doppler frequency offset causes a carrier frequency shift in the received signal, and FFT can separate different frequency components, when the local pseudo-random sequence is aligned with the code phase of the received signal, the time-domain sequence output by the PMF approximates a single-frequency signal with a frequency equal to the residual Doppler frequency offset. This single-frequency signal, after FFT, will form a peak at the corresponding frequency position. Therefore, by detecting the peak position in the frequency domain energy spectrum, the Doppler frequency offset can be estimated; simultaneously, the code phase corresponding to this peak is the captured code phase.

[0047] Optionally, to offset the increased computational load of the FFT due to zero-padding, a processing clock with a frequency higher than the sampling rate (e.g., 80MHz or 160MHz) can be used to perform the N-point FFT. Taking an 80MHz clock and an 8192-point FFT as an example, the latency of a single FFT operation is approximately 0.47ms, which is much smaller than the coherent integration time (20ms) and does not affect the real-time acquisition performance. The specific frequency of the fast clock can be selected based on a combination of FPGA resources and power consumption requirements: when resources are ample, using 160MHz can further shorten the latency, while using 80MHz can also meet the requirements when resources are limited.

[0048] Step S4: Perform non-coherent accumulation on the frequency domain energy spectrum output from multiple consecutive N-point Fast Fourier Transforms to obtain the accumulated energy spectrum.

[0049] At extremely low carrier-to-noise ratios (e.g., -30 dBHz), signal peaks in a single FFT energy spectrum are often submerged in noise and cannot pass threshold decision. This application performs noncoherent accumulation of the frequency domain energy spectrum from multiple consecutive N-point Fast Fourier Transform outputs, making the signal peaks stand out. This is because noise is random, and after multiple accumulations, the average power of the noise tends to stabilize, reducing fluctuations. In contrast, the signal is deterministic, and its peak value increases linearly (amplitude accumulation) or quadratically (energy accumulation) with the number of accumulations. Therefore, the distinction between signal and noise is greatly improved.

[0050] Taking 100 noncoherent accumulation iterations as an example, under the same code phase assumption, steps S2 to S3 are repeated 100 times (i.e., processing 100 consecutive 20ms time blocks, with a total duration of 2 seconds). The magnitude of each FFT output is accumulated to obtain the accumulated energy spectrum. Noncoherent accumulation improves the signal-to-noise ratio by approximately 10log. 10 (100) = 20dB. After 100 noncoherent accumulations, the signal with a carrier-to-noise ratio of -30dBHz becomes detectable.

[0051] Noncoherent accumulation is one of the core techniques used in this application to achieve reliable acquisition in extremely low carrier-to-noise ratio environments. By accumulating the energy of multiple independently measured signals, it effectively improves the separation between signal and noise, solves the problem of insufficient sensitivity in a single PMF-FFT, and maintains the simplicity of engineering implementation.

[0052] Step S5: Extract the principal maximum modulus, the secondary maximum modulus, and the average modulus of all energy spectral points from the accumulated energy spectrum.

[0053] In the accumulated energy spectrum, the maximum value is searched to obtain the principal maximum modulus Pimax0, the second largest value is searched to obtain the secondary maximum modulus Pimax1, and the arithmetic mean Piavg of the modulus values ​​at all frequencies is calculated.

[0054] Step S6: Determine whether the following conditions are met simultaneously: the ratio of the principal maximum modulus to the average modulus is greater than the first threshold, and the ratio of the principal maximum modulus to the secondary maximum modulus is greater than the second threshold.

[0055] Determine whether the following conditions are met simultaneously: Pimax0 / Piavg > Th1; Pimax0 / Pimax1 > Th2.

[0056] The arithmetic mean of the magnitudes at all frequencies, Piavg, reflects the average level of the current noise floor. The principal maximum magnitude, Pimax0, is the maximum value in the accumulated energy spectrum, which may originate from a real signal or a noise spike. The ratio Pimax0 / Piavg indicates the prominence of the signal peak relative to the average noise. When this ratio is greater than the first threshold Th1, it indicates that the peak is significantly higher than the noise floor and is likely a real signal rather than noise.

[0057] The second-largest modulus, Pimax1, is the second-largest peak in the energy spectrum. The ratio Pimax0 / Pimax1 represents the dominance of the main peak relative to the second-largest peak. When this ratio is greater than the second threshold Th2, it indicates that the main peak is much higher than any other peak, thus ruling out the following two possibilities: Pseudo-code autocorrelation side peaks: The autocorrelation function of some pseudo-random sequences has side peaks, the height of which may be close to the main peak. If the main peak is a side peak, the ratio may be low. FFT sidelobes: Due to spectral leakage, a strong signal may produce high sidelobes at adjacent frequency points. If the main peak is a side lobe, the second-largest (main lobe) may be close to or even higher. In incoherent spread spectrum systems, pseudo-code autocorrelation side peaks may mislead the receiver into locking to the wrong phase. The second threshold directly detects the main / second-largest ratio, effectively avoiding locking to the side peak. For the main lobe broadening caused by FFT scalloping loss, the second threshold can also prevent side lobes from being misjudged as main peaks.

[0058] If both conditions are met, the process proceeds to the successful acquisition branch in step S7; otherwise, it proceeds to the failure branch. A valid signal acquisition is only considered successful when the main peak is significantly higher than the noise floor (first condition) and significantly higher than all other peaks (second condition). If either condition is not met, it is considered a false alarm or false lock, and the sliding code phase continues. The combined use of these two conditions allows the overall false alarm probability to be controlled within 10%. -6 The following methods are far superior to single-threshold methods.

[0059] Optionally, Th1 = 24, Th2 = 1.25. The main maxima ratio is greater than 24 times the average to maximize the acquisition threshold and sensitivity, and the main maxima ratio is greater than 1.25 times the secondary maxima ratio to prevent false acquisition under high signal-to-noise ratio.

[0060] Step S7: If the conditions are met, the acquisition is considered successful, and the current code phase and Doppler frequency estimate are output; if the conditions are not met, the phase of the local pseudo-random sequence is adjusted, and the process returns to step S2 until the acquisition is successful or the maximum number of attempts is reached.

[0061] If the decision is successful, the starting code phase (i.e., code phase estimate) of the current local pseudo-random sequence and the frequency index corresponding to the main maxima (i.e., Doppler frequency coarse estimate) are output, and the capture ends.

[0062] If the decision fails, the starting code phase of the local pseudo-random sequence is shifted by one chip (i.e., the entire sequence is shifted one chip to the right), and then the process is returned to step S2 and repeated. If the process fails after 1023 shifts (i.e., traversing all code phases), it is determined that there is no signal or the acquisition has timed out.

[0063] The estimated acquisition time of the spread spectrum signal in this application is as follows: the effective integration time is 20ms. Using an 80MHz fast clock with a base-4 8192-point FFT soft core, the estimated delay is 0.47ms. Post-processing analysis of the PMF-FFT output result shows a Tc of approximately 0.2ms (8192 times). Therefore, the total calculation time is approximately 20.67ms, with a total of 1023 code points. With the initial phase at a random position, the expected time for a single scan is approximately 10.58 seconds.

[0064] In some embodiments, to further reduce the acquisition time, multiple acquisition channels are scanned in parallel. Taking two acquisition channels as an example, for a total length M=1023 of the local pseudo-random sequence, the start code phase of the local pseudo-random sequence in the first acquisition channel is set to 0, and the start code phase of the second acquisition channel is set to 512. The first acquisition channel scans the interval 0 to 511, and the second acquisition channel scans the interval 512 to 1022. Each acquisition channel independently and in parallel executes the above steps S2 to S6. When the dual threshold decision of any channel passes, the control logic immediately sends a stop signal to all channels and outputs the code phase and Doppler estimate of that channel, indicating successful overall acquisition. Using dual-channel parallel scanning, the acquisition time is approximately half that of single-channel serial scanning. If FPGA resources allow, the number of channels can be further increased (e.g., K=4, 12, etc.), and the acquisition time is correspondingly shortened to 1 / K of that of a single channel.

[0065] In some embodiments, to further reduce the false alarm probability, a Down syndrome detection strategy is introduced in step S6. Specifically: First dwell: Use a lower first threshold Th1_low=8 and a second threshold Th2_low=1.1 to perform a double threshold decision on the current code phase. If satisfied, record the code phase as a candidate unit.

[0066] Second dwell: For each candidate cell, using a higher first threshold Th1_high=24 and a second threshold Th2_high=1.25, steps S2 to S6 are executed again (a longer coherent integral or more non-coherent accumulation may be used). Only cells that satisfy the dual threshold conditions in two consecutive dwells are considered successfully captured.

[0067] If the second dwell fails, the candidate cell is abandoned, and other phases are scanned. Tang detection reduces the final false alarm probability to 10%. -6 The following also maintained a high detection probability.

[0068] Those skilled in the art will understand that the present invention is not limited to the specific embodiments described above. For example, the PMF length L can be selected in the range of 11 to 31. Figure 3 This is a graph showing the effect of different matched filter lengths on gain according to an embodiment of this application. Figure 3As shown, the horizontal axis represents the Doppler frequency difference, and the vertical axis represents the normalized gain magnitude. It can be seen that when L is 93 (corresponding to the first curve 301), the gain drops rapidly when the Doppler frequency difference deviates significantly. When L is 31 (corresponding to the second curve 302), the gain decreases more slowly when the Doppler frequency difference deviates significantly. At L=11 (corresponding to the third curve 303), the 3dB bandwidth of the gain is close to 100kHz. Therefore, under the premise of reducing resource consumption and the number of acquisition channels, the PMF length L can be selected within the range of 11 to 31.

[0069] Compared with the prior art, this application has the following beneficial effects: 1) Significantly improved sensitivity: By forcing noncoherent accumulation, the energy spectrum of multiple PMF-FFT outputs is accumulated, which effectively improves the detection signal-to-noise ratio and can adapt to a carrier-to-noise ratio of -30dBHz or even lower, while conventional PMF-FFT can hardly work under the same conditions.

[0070] 2) Significantly reduced false alarm rate: A dual threshold decision is adopted (primary maxima / mean ratio and primary maxima / secondary maxima ratio), and both conditions must be met simultaneously. The first threshold ensures that the primary peak is significantly higher than the noise floor, and the second threshold ensures that the primary peak is not a pseudo-code secondary peak or an FFT sidelobe.

[0071] 3) Strong resistance to scallop loss: By padding zeros to expand the number of FFT points, the frequency resolution is further refined, reducing scallop loss and significantly improving the frequency estimation accuracy and detection probability.

[0072] 4) Excellent real-time acquisition performance: The FFT is performed using a fast clock (80MHz or 160MHz), which offsets the additional computational delay caused by zero padding. At the same time, the multi-path parallel scanning strategy can further shorten the acquisition time, meeting the second-level response requirements of scientific experimental satellites.

[0073] 5) Low hardware resource overhead: By combining a partially matched filter array with FFT and an optional multi-channel parallel architecture, it can be flexibly configured according to FPGA resources to meet the miniaturization and low power consumption requirements of deep space satellites.

[0074] The spread spectrum signal rapid acquisition method and system provided in this application can be applied to fields such as deep space exploration and satellite communication, and is particularly suitable for spread spectrum telemetry and control transponders in resource-constrained, high-dynamic, and low-signal-noise-ratio environments such as DRO satellites. This is because DRO (Distant Retrograde Orbit) satellites are approximately 310,000 to 450,000 kilometers from Earth, resulting in significant signal attenuation in space. Ground station EIRP and G / T values ​​are limited, and the onboard receiver carrier-to-noise ratio can be as low as -30 dBHz. The relative velocity between the satellite and the ground can reach 12.8 km / s, generating ±450 kHz Doppler frequency offset and a rate of change of 5 kHz / s. Due to the small size, tight power consumption budget, and cost sensitivity of satellites, traditional deep space transponders (such as the large-volume, high-power devices of the UXB system) cannot be installed. This application, through a combination of noncoherent accumulation, dual thresholding, zero-filled fast clock PMF-FFT, and multi-channel parallel scanning, achieves second-level, highly reliable, and low-false alarm spread spectrum acquisition of the DRO satellite platform under dynamic conditions of -30 dBHz and ±450 kHz, under controllable resource consumption, and is therefore particularly suitable for this type of mission.

[0075] Flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, various steps can be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more steps may be removed from these processes.

[0076] Furthermore, it should be noted that the use of terms such as "first" and "second" to define components is merely for the purpose of distinguishing the corresponding components. Unless otherwise stated, these terms have no special meaning and therefore should not be construed as limiting the scope of protection of this application. In addition, although the terminology used in this application is selected from commonly known and used terms, some terms mentioned in this application's specification may have been chosen by the applicant according to his or her judgment, and their detailed meanings are explained in the relevant sections of this description. Moreover, this application should be understood not only through the actual terms used, but also through the meaning implied by each term.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of the present invention.

[0078] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0079] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A spread spectrum signal acquisition method suitable for high dynamic range, low carrier-to-noise ratio scenarios, characterized in that, include: Step S1: Receive the spread spectrum signal and sample it at a preset sampling rate to obtain the digital baseband signal; Step S2: Using a partially matched filter array composed of multiple partially matched filters, the digital baseband signal and the local pseudo-random sequence are segmented and correlated in parallel to output multiple partial correlation results; Step S3: Perform an N-point Fast Fourier Transform on the multi-path partial correlation results to obtain the frequency domain energy spectrum, where N is a power of 2; Step S4: Perform non-coherent accumulation on the frequency domain energy spectrum of the N-point Fast Fourier Transform output multiple times to obtain the accumulated energy spectrum; Step S5: Extract the principal maximum modulus, the secondary maximum modulus, and the average modulus of all energy spectrum points from the accumulated energy spectrum. Step S6: Determine whether the following conditions are met simultaneously: the ratio of the principal maximum modulus to the average modulus is greater than a first threshold, and the ratio of the principal maximum modulus to the secondary maximum modulus is greater than a second threshold; Step S7: If the conditions are met, the acquisition is considered successful, and the current code phase and Doppler frequency estimate are output; if the conditions are not met, the phase of the local pseudo-random sequence is adjusted, and the process returns to step S2 until the acquisition is successful or the maximum number of attempts is reached.

2. The method as described in claim 1, characterized in that, The partially matched filter array contains P partially matched filters, each with a length of L, and satisfies P×L = M, where M is the total length of the local pseudo-random sequence.

3. The method as described in claim 2, characterized in that, The length L of the partially matched filter ranges from 11 to 31.

4. The method as described in claim 1, characterized in that, Before performing the N-point Fast Fourier Transform, the method further includes: zero-padding the multi-path partial correlation results to N points to refine the frequency resolution and reduce the scallop loss caused by the deviation of the true Doppler frequency from the discrete frequency points.

5. The method as described in claim 1, characterized in that, The N-point Fourier transform is performed using a processing clock with a frequency higher than the sampling rate.

6. The method as described in claim 1, characterized in that, In step S7, multiple parallel capture channels are used, each capture channel corresponds to a different start code phase of the local pseudo-random sequence, and each capture channel executes steps S2 to S6 in parallel; when any capture channel successfully captures, all capture channels are stopped and the overall capture is determined to be successful.

7. The method as described in claim 6, characterized in that, The plurality of parallel capture channels include a first capture channel and a second capture channel. The first capture channel scans from code phase 0 of the local pseudo-random sequence, and the second capture channel scans from code phase 512.

8. The method as described in claim 1, characterized in that, The decision in step S6 adopts the Tang detection strategy, which includes: in each dwell stage, the first threshold and the second threshold are used for decision making, and the first threshold and / or the second threshold have different values ​​in different dwell stages.

9. The method as described in claim 1, characterized in that, The first threshold is 24, and the second threshold is 1.

25.

10. A spread spectrum signal acquisition system suitable for high dynamic range, low carrier-to-noise ratio scenarios, characterized in that, include: The sampling module is used to receive the spread spectrum signal and sample it at a preset sampling rate to obtain the digital baseband signal; The partially matched filter array module, composed of multiple partially matched filters, is used to perform segmented parallel correlation between the digital baseband signal and the local pseudo-random sequence, and output multiple partial correlation results. The Fourier transform module is used to perform an N-point Fourier transform on the multi-path partial correlation results to obtain the frequency domain energy spectrum, where N is a power of 2. The noncoherent accumulation module, connected to the Fourier transform module, is used to noncoherently accumulate the frequency domain energy spectrum of the N-point fast Fourier transform output multiple times to obtain the accumulated energy spectrum. The peak detection module, connected to the non-coherent accumulation module, is used to extract the principal maximum modulus, the secondary maximum modulus, and the average modulus value of all energy spectral points from the accumulated energy spectrum. A dual threshold decision module is used to determine whether the following conditions are met simultaneously: the ratio of the principal maximum modulus to the average modulus is greater than a first threshold, and the ratio of the principal maximum modulus to the secondary maximum modulus is greater than a second threshold. The control and phase scanning module is connected to the partially matched filter array module and the dual threshold decision module, respectively. When the decision is not satisfied, the phase of the local pseudo-random sequence is adjusted and the partially matched filter array module is re-triggered until the acquisition is successful or the maximum number of attempts is reached. When the decision is satisfied, the current code phase and Doppler frequency estimate are output.

11. The system as claimed in claim 10, characterized in that, The partially matched filter array module contains P partially matched filters, each with a length of L, and satisfies P×L = M, where M is the total length of the local pseudo-random sequence.

12. The system as claimed in claim 10, characterized in that, The Fourier transform module also includes a zero-padding unit, which is used to zero-padding the multi-path partial correlation results to N points before performing the N-point fast Fourier transform, so as to refine the frequency resolution and reduce the scallop loss caused by the deviation of the true Doppler frequency from the discrete frequency points.

13. The system as described in claim 10, characterized in that, The control and phase scanning module is configured to employ multiple parallel acquisition channels, each corresponding to a different start code phase of the local pseudo-random sequence. Each acquisition channel triggers the partially matched filter array module, Fourier transform module, non-coherent accumulation module, peak detection module, and dual threshold decision module in parallel. When any acquisition channel successfully acquires, all acquisition channels are stopped and the overall acquisition is determined to be successful.

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