A low signal-to-noise ratio periodic linear frequency modulation continuous wave signal detection method and system

Abstract

This invention discloses a method and system for detecting low signal-to-noise ratio periodic linear frequency modulated (LFM) continuous wave signals, relating to the fields of radio target monitoring and spectrum management. The method includes: detecting periodic components in the data to be detected; if periodic components exist, recording period estimates based on these components; determining two adjacent observation windows based on the difference between the period estimates and the delay, and the delay itself; dividing the data to be detected into P consecutive groups of data using the period estimates; using a sampling point as the starting position of a step-size sliding observation window, performing piecewise discrete polynomial transformation and spectrum calculation on the data to be detected corresponding to each step-size sliding observation window, thereby detecting the periodic LFM continuous wave signal; when the detection result indicates the presence of a periodic LFM continuous wave signal, determining the modulation slope and modulation inflection point position of the signal. This invention effectively improves the detection capability for weak periodic LFM continuous wave signals.

Description

Technical Field

[0001] This invention relates to the fields of radio target monitoring and spectrum management, and in particular to a method and system for detecting low signal-to-noise ratio periodic linear frequency modulated continuous wave signals. Background Technology

[0002] Efficient detection and parameter estimation of periodic linear frequency modulated (LFM) continuous wave (CFW) signals are essential for radio target monitoring and spectrum management. In recent years, the rapid development of electronic information technology has brought new challenges to the detection of LFM signals in electromagnetic spectrum monitoring systems. For example, the increasing number of frequency-using devices has led to a more congested electromagnetic spectrum, resulting in more complex environmental noise, increased receiver noise floor, and a lower signal-to-noise ratio (SNR) of the detected signal. Furthermore, the widely used high-carrier frequency LFM W signals exhibit greater path loss. Traditional low SNR LFM W signal detection methods are computationally complex and difficult to deploy on small devices, all of which contribute to a decrease in receiver detection range. Summary of the Invention

[0003] The purpose of this invention is to provide a method and system for detecting low signal-to-noise ratio periodic linear frequency modulated continuous wave signals, which can solve the problem of energy dispersion in LFMCW signal detection based on traditional discrete polynomial transform, making it difficult to apply to low signal-to-noise ratio scenarios, thereby effectively improving the detection capability of weak periodic linear frequency modulated continuous wave signals.

[0004] To achieve the above objectives, the present invention provides the following solution:

[0005] A method for detecting low signal-to-noise ratio periodic linear frequency modulated continuous wave signals includes:

[0006] Acquire the data to be detected; and perform periodic component detection on the data to be detected;

[0007] If a periodic component exists, the period estimate is recorded based on the periodic component; and the delay is set based on the period estimate.

[0008] Two adjacent observation windows are determined based on the difference between the period estimate and the delay, and the delay itself.

[0009] The data to be detected is divided into P continuous groups using the period estimate; P is the maximum number of groups.

[0010] Using a sampling point as the starting position of the step-size sliding observation window, piecewise discrete polynomial transformation and spectrum calculation are performed on the data to be detected corresponding to each step-size sliding observation window;

[0011] The periodic linear frequency modulated continuous wave signal in the data to be detected is determined based on the maximum value of the spectrum and the corresponding frequency at each step size.

[0012] When the detection result indicates the presence of a periodic linear frequency modulated continuous wave signal, the frequency modulation slope and frequency modulation inflection point position of the periodic linear frequency modulated continuous wave signal are calculated based on the frequency and step size corresponding to the maximum value of the spectrum.

[0013] Optionally, the data to be detected is digitally processed intermediate frequency or baseband data.

[0014] Optionally, the delay τ ≤ T e / 2; where T e This is a periodic estimate.

[0015] Optionally, the step of dividing the data to be detected into P consecutive groups of data using the period estimate further includes:

[0016] Zero-padding is applied to the data segmented from the shorter observation window among two adjacent observation windows.

[0017] Optionally, the step of using a sampling point as the starting position of the sliding observation window, and performing piecewise discrete polynomial transformation and spectrum calculation on the data to be detected corresponding to each step of the sliding observation window, specifically includes:

[0018] The qth sliding observation window: when T e ×(p-1)+q≤n <T e ×(p-1)+q+(T e When -τ), use formula d1 p (l1) = x(n)·x*(n-τ) yields the transformation sequence d1p; where d1p = [d1p(1), d1p(2), d1p(3), ...], d1 p (l1) represents the l1-th data point of the discrete polynomial transform of the first segment within the length of the p-th periodic estimate, where l1 = (n mod T) e )-q+1,(n modT e ) represents n divided by T e Take the remainder, * indicates taking the conjugate, q is the sliding index, and T e Here, τ is the period estimate, τ is the delay, and n is the nth sampling point;

[0019] After downsampling the transform sequence d1p, perform a fast Fourier transform and take the modulus to obtain the spectrum f1p of the first discrete polynomial transform within the length of the p-th period estimate.

[0020] When T e ×p+q-τ≤n <T e When ×p, use formula d2 p(l2) = x(n)·x*(n+τ) yields the transformation sequence d2p; where d2p = [d2p(1), d2p(2), d2p(3), ...], d2 p (l2) represents the l2th data point in the second discrete polynomial transform within the length of the p-th periodic estimate, where l2 = (n mod T) e )+τ-qT e +1);

[0021] The transformed sequence d2p is padded with zeros at the end to make its data length equal to that of d1p. Then it is downsampled, and then a fast Fourier transform is performed and the modulus is taken to obtain the spectrum f2p of the second discrete polynomial transform within the length of the p-th period estimate.

[0022] The sum of the spectra of each discrete polynomial transformation within the length of each period estimate is used to obtain the sum spectrum fq corresponding to the qth sliding observation window.

[0023] Optionally, the detection of the periodic linear frequency modulated continuous wave signal in the data to be detected based on the maximum value of the spectrum and the corresponding frequency at each step size specifically includes:

[0024] Determine the step size condition corresponding to the maximum value in the spectrum;

[0025] Determine whether the sum of the spectrum of the maximum value corresponds to the step size condition on both sides of the maximum step size condition has a maximum value;

[0026] If present, the data to be detected is determined to contain a periodic linear frequency modulated continuous wave signal;

[0027] If it does not exist, it is determined that the data to be detected does not contain a periodic linear frequency modulated continuous wave signal.

[0028] A low signal-to-noise ratio periodic linear frequency modulated continuous wave signal detection system includes:

[0029] The periodic component detection module is used to acquire the data to be detected and to perform periodic component detection on the data to be detected.

[0030] The delay setting module is used to record the estimated period value based on the periodic component if a periodic component exists, and to set the delay amount based on the estimated period value.

[0031] The observation window determination module is used to determine two adjacent observation windows based on the difference between the period estimate and the delay, and the delay itself.

[0032] The grouping module is used to divide the data to be detected into P consecutive groups of data using the period estimate; P is the maximum number of groups.

[0033] The calculation module is used to perform piecewise discrete polynomial transformation and spectrum calculation on the data to be detected corresponding to each step of the sliding observation window, with a sampling point as the starting position of the sliding observation window.

[0034] The periodic linear frequency modulated continuous wave signal detection module is used to detect the periodic linear frequency modulated continuous wave signal in the data to be detected based on the maximum value of the spectrum and the corresponding frequency at each step size.

[0035] The frequency modulation slope and frequency modulation inflection point location determination module is used to calculate the frequency modulation slope and frequency modulation inflection point location of the periodic linear frequency modulation continuous wave signal based on the frequency and step size corresponding to the maximum value of the spectrum when the detection result is that there is a periodic linear frequency modulation continuous wave signal.

[0036] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0037] The present invention provides a method and system for detecting low signal-to-noise ratio periodic linear frequency modulated (LFM) continuous wave signals. First, periodic components are detected and period values ​​are estimated in the data to be detected; if periodic components are present, the estimated period value is recorded. Second, a delay is set based on the estimated period value, and two adjacent observation windows are selected with lengths equal to the estimated period value minus the delay and the delay value, respectively. The starting position of the observation window is slidable with a step size as one sampling point. Each time the observation window is slidable, a piecewise discrete polynomial transform is performed on the intermediate frequency or baseband data of the required observation length, and the sum and spectrum are calculated. Then, based on the maximum value of the sum and spectrum under each step size and its corresponding frequency, it is determined whether the data to be detected contains a periodic LFM continuous wave signal. Finally, the frequency modulation slope and frequency modulation inflection point position of the LFM continuous wave signal are calculated based on the frequency corresponding to the maximum value of the sum and spectrum and the step size. This invention addresses the problem of energy dispersion in LFMCW signal detection based on traditional discrete polynomial transform, which makes it unsuitable for low signal-to-noise ratio (SNR) scenarios. It effectively improves the detection capability for weak-period linear frequency modulated (LFMCW) signals. Compared to existing methods for detecting low SNR periodic LFMCW signals, this invention does not involve multi-dimensional parallel data transformation and parameter search. Furthermore, it uses oversampling after the discrete polynomial transform to further reduce the data volume, resulting in lower computational complexity. Under comparable computational requirements, compared to periodic fractional Fourier transform and periodic Wegener-Hough transform algorithms, the proposed algorithm improves the detection SNR gain factor by approximately 60 dB and increases the receiver detection range by approximately 400 times. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. 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.

[0039] Figure 1 This is a schematic diagram of a low signal-to-noise ratio periodic linear frequency modulated continuous wave signal detection method provided by the present invention;

[0040] Figure 2 This is a schematic diagram illustrating the principle of a low signal-to-noise ratio periodic linear frequency modulated continuous wave signal detection method provided by the present invention. Detailed Implementation

[0041] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] The purpose of this invention is to provide a method and system for detecting low signal-to-noise ratio periodic linear frequency modulated continuous wave signals, which can solve the problem of energy dispersion in LFMCW signal detection based on traditional discrete polynomial transform, making it difficult to apply to low signal-to-noise ratio scenarios, thereby effectively improving the detection capability of weak periodic linear frequency modulated continuous wave signals.

[0043] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0044] like Figure 1 and Figure 2 As shown, the present invention provides a method for detecting low signal-to-noise ratio periodic linear frequency modulated continuous wave signals, comprising:

[0045] S101, acquire the data to be detected; and perform periodic component detection on the data to be detected; the data to be detected is intermediate frequency or baseband data after digital processing.

[0046] S102, if a periodic component exists, then record the estimated period value based on the periodic component; and set a delay amount based on the estimated period value; the delay amount τ≤T e / 2; where T e This is a periodic estimate.

[0047] S103, the difference between the estimated period and the delay (T) e-τ) and the delay (τ) determine two adjacent observation windows.

[0048] S104, using the period estimate, divide the data to be detected into P continuous groups of data; P is the maximum number of groups.

[0049] Following S104 are:

[0050] Zero-padding is performed on the data segmented from the shorter observation window in two adjacent observation windows to make the two sets of data the same length. The segmented data are then subjected to Fast Fourier Transform and the modulus is taken to obtain the spectrum of each segment.

[0051] S105, taking a sampling point as the starting position of the step-size sliding observation window, performs piecewise discrete polynomial transformation and spectrum calculation on the data to be detected corresponding to each step-size sliding observation window;

[0052] The observation window is slidable with a step size as the starting position of a sampling point. Each time the observation window is slidable, the downsampled data is segmented using the observation window. Zeros are padded to make the data segments of the shorter window the same length. Fast Fourier Transform is performed on the segmented data, and the modulus is taken to obtain the spectrum of each segment. The spectra of each segment are then added together to obtain the sum spectrum corresponding to each sliding observation window. The maximum spectral value and its position are recorded. Finally, the previous step is repeated. If the positions of the maximum spectral values ​​are the same, it is determined that the data to be detected contains a linear frequency modulated continuous wave signal, and the frequency modulation slope of the linear frequency modulated continuous wave signal is calculated according to the discrete polynomial transform characteristics.

[0053] S105 specifically includes:

[0054] The qth sliding observation window: when T e ×(p-1)+q≤n <T e ×(p-1)+q+(T e When -τ), use formula d1 p (l1) = x(n)·x*(n-τ) yields the transformation sequence d1p; where d1p = [d1p(1), d1p(2), d1p(3), ...], d1 p (l1) represents the l1-th data point of the discrete polynomial transform of the first segment within the length of the p-th periodic estimate, where l1 = (n mod T) e )-q+1,(n modT e ) represents n divided by T e Take the remainder, * indicates taking the conjugate, q is the sliding index, and T e Let τ be the period estimate, τ be the delay, and n be the nth sampling point.

[0055] After downsampling the transformed sequence d1p, perform a fast Fourier transform and take the modulus to obtain the spectrum f1p of the first discrete polynomial transform within the length of the p-th period estimate.

[0056] When T e ×p+q-τ≤n <T e When ×p, use formula d2 p (l2) = x(n)·x*(n+τ) yields the transformation sequence d2p; where d2p = [d2p(1), d2p(2), d2p(3), ...], d2 p (l2) represents the l2th data point in the second discrete polynomial transform within the length of the p-th periodic estimate, where l2 = (n mod T) e )+τ-qT e +1).

[0057] The transformed sequence d2p is padded with zeros at the end to make its data length equal to that of d1p. Then, it is downsampled, and then a fast Fourier transform is performed and the modulus is taken to obtain the spectrum f2p of the second discrete polynomial transform within the length of the p-th period estimate.

[0058] The sum of the spectra of each discrete polynomial transformation within the length of each period estimate is used to obtain the sum spectrum fq corresponding to the qth sliding observation window.

[0059] S106, Detect the periodic linear frequency modulated continuous wave signal in the data to be detected based on the maximum value of the spectrum and the corresponding frequency at each step size.

[0060] S106 specifically includes:

[0061] Determine the step size condition corresponding to the maximum value in the spectrum.

[0062] Determine if the sum of the sums of the spectra of the two adjacent step sizes corresponding to the maximum value of the sum spectrum has a maximum value.

[0063] If present, the data to be detected is determined to contain a periodic linear frequency modulated continuous wave signal.

[0064] If it does not exist, it is determined that the data to be detected does not contain a periodic linear frequency modulated continuous wave signal.

[0065] S107, when the detection result indicates the presence of a periodic linear frequency modulated continuous wave signal, calculate the frequency modulation slope and frequency modulation inflection point position of the periodic linear frequency modulated continuous wave signal based on the frequency and step size corresponding to the maximum value of the spectrum.

[0066] Corresponding to the above method, the present invention also provides a low signal-to-noise ratio periodic linear frequency modulated continuous wave signal detection system, comprising:

[0067] The periodic component detection module is used to acquire the data to be detected and to perform periodic component detection on the data to be detected.

[0068] The delay setting module is used to record the estimated period value based on the periodic component if a periodic component exists, and to set the delay amount based on the estimated period value.

[0069] The observation window determination module is used to determine two adjacent observation windows based on the difference between the period estimate and the delay, and the delay itself.

[0070] The grouping module is used to divide the data to be detected into P consecutive groups of data using the period estimate; P is the maximum number of groups.

[0071] The calculation module is used to perform piecewise discrete polynomial transformation and spectrum calculation on the data to be detected corresponding to each step of the sliding observation window, with a sampling point as the starting position.

[0072] The periodic linear frequency modulated continuous wave signal detection module is used to detect periodic linear frequency modulated continuous wave signals in the data to be detected based on the maximum value of the spectrum and the corresponding frequency at each step size.

[0073] The frequency modulation slope and frequency modulation inflection point location determination module is used to calculate the frequency modulation slope and frequency modulation inflection point location of the periodic linear frequency modulation continuous wave signal based on the frequency and step size corresponding to the maximum value of the spectrum when the detection result is that there is a periodic linear frequency modulation continuous wave signal.

[0074] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0075] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for detecting low signal-to-noise ratio periodic linear frequency modulated continuous wave signals, characterized in that, include: Acquire the data to be tested; And perform periodic component detection on the data to be tested; If a periodic component exists, then the periodic estimate is recorded based on the periodic component. And set the delay amount based on the cycle estimate; Two adjacent observation windows are determined based on the difference between the period estimate and the delay, and the delay itself. The data to be detected is divided into P continuous groups using the period estimate; P is the maximum number of groups. Using a sampling point as the starting position of the step-size sliding observation window, piecewise discrete polynomial transformation and spectrum calculation are performed on the data to be detected corresponding to each step-size sliding observation window; The periodic linear frequency modulated continuous wave signal in the data to be detected is determined based on the maximum value of the spectrum and the corresponding frequency at each step size. When the detection result indicates the presence of a periodic linear frequency modulated continuous wave signal, the frequency modulation slope and frequency modulation inflection point position of the periodic linear frequency modulated continuous wave signal are calculated based on the frequency and step size corresponding to the maximum value of the spectrum.

2. The method for detecting low signal-to-noise ratio periodic linear frequency modulated continuous wave signals according to claim 1, characterized in that, The data to be detected is digitized intermediate frequency or baseband data.

3. The method for detecting low signal-to-noise ratio periodic linear frequency modulated continuous wave signals according to claim 1, characterized in that, The delay τ≤T e / 2; where T e This is a periodic estimate.

4. The method for detecting low signal-to-noise ratio periodic linear frequency modulated continuous wave signals according to claim 1, characterized in that, The process of dividing the data to be detected into P consecutive groups using the period estimate further includes: Zero-padding is applied to the data segmented from the shorter observation window among two adjacent observation windows.

5. The method for detecting low signal-to-noise ratio periodic linear frequency modulated continuous wave signals according to claim 1, characterized in that, The process of using a sampling point as the starting position of the sliding observation window and performing piecewise discrete polynomial transformation and spectrum calculation on the data to be detected corresponding to each sliding observation window at each step size specifically includes: The qth sliding observation window: when T e ×(p-1)+q≤n <T e ×(p-1)+q+(T e When -τ), use formula d1 p (l1) = x(n)·x*(n-τ) yields the transformation sequence d1p; where d1p = [d1p(1), d1p(2), d1p(3), ...], d1 p (l1) represents the l1-th data point of the discrete polynomial transform of the first segment within the length of the p-th periodic estimate, where l1 = (n mod T) e )-q+1,(n modT e ) represents n divided by T e Take the remainder, * indicates taking the conjugate, q is the sliding index, and T e Here, τ is the period estimate, τ is the delay, and n is the nth sampling point; After downsampling the transform sequence d1p, perform a fast Fourier transform and take the modulus to obtain the spectrum f1p of the first discrete polynomial transform within the length of the p-th period estimate. When T e ×p+q-τ≤n <T e When ×p, use formula d2 p (l2) = x(n)·x*(n+τ) yields the transformation sequence d2p; where d2p = [d2p(1), d2p(2), d2p(3), ...], d2 p (l2) represents the l2th data point in the second discrete polynomial transform within the length of the p-th periodic estimate, where l2 = (n mod T) e )+τ-qT e +1); The transformed sequence d2p is padded with zeros at the end to make its data length equal to that of d1p. Then it is downsampled, and then a fast Fourier transform is performed and the modulus is taken to obtain the spectrum f2p of the second discrete polynomial transform within the length of the p-th period estimate. The sum of the spectra of each discrete polynomial transformation within the length of each period estimate is used to obtain the sum spectrum fq corresponding to the qth sliding observation window.

6. The method for detecting low signal-to-noise ratio periodic linear frequency modulated continuous wave signals according to claim 1, characterized in that, The detection of periodic linear frequency modulated continuous wave signals in the data to be detected based on the maximum value of the spectrum and the corresponding frequency at each step size specifically includes: Determine the step size condition corresponding to the maximum value in the spectrum; Determine whether the sum of the spectrum of the maximum value corresponds to the step size condition on both sides of the maximum step size condition has a maximum value; If present, the data to be detected is determined to contain a periodic linear frequency modulated continuous wave signal; If it does not exist, it is determined that the data to be detected does not contain a periodic linear frequency modulated continuous wave signal.

7. A low signal-to-noise ratio periodic linear frequency modulated continuous wave signal detection system, characterized in that, include: The periodic component detection module is used to acquire the data to be detected; And perform periodic component detection on the data to be tested; The delay setting module is used to record the estimated period value based on the periodic component if a periodic component exists, and to set the delay amount based on the estimated period value. The observation window determination module is used to determine two adjacent observation windows based on the difference between the period estimate and the delay, and the delay itself. The grouping module is used to divide the data to be detected into P consecutive groups of data using the period estimate; P is the maximum number of groups. The calculation module is used to perform piecewise discrete polynomial transformation and spectrum calculation on the data to be detected corresponding to each step of the sliding observation window, with a sampling point as the starting position of the sliding observation window. The periodic linear frequency modulated continuous wave signal detection module is used to detect the periodic linear frequency modulated continuous wave signal in the data to be detected based on the maximum value of the spectrum and the corresponding frequency at each step size. The frequency modulation slope and frequency modulation inflection point location determination module is used to calculate the frequency modulation slope and frequency modulation inflection point location of the periodic linear frequency modulation continuous wave signal based on the frequency and step size corresponding to the maximum value of the spectrum when the detection result is that there is a periodic linear frequency modulation continuous wave signal.

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