Intermittent sampling and forwarding interference identification and suppression method based on differential characteristics

Abstract

The present invention discloses an intermittent sampling forwarding interference identification and suppression method based on differential features, comprising: extracting differential features of radar receiving signals; performing conventional detection on the result of the first-order differential features after passing through a square law detector and a threshold γ to obtain an alternative signal source; performing interference identification on the alternative signal source by utilizing the difference between a target echo and an interference signal in a differential feature space; and outputting a target detection result. The present invention can effectively realize target detection in an intermittent sampling forwarding interference scenario.

Description

Technical Field

[0001] The invention belongs to the technical field of radar electronic countermeasures, and in particular relates to an intermittent sampling forwarding interference identification and suppression method based on differential characteristics. Background Art

[0002] The electromagnetic environment faced by modern radars is becoming increasingly complex, and the types of interference are constantly enriched, which seriously restricts the detection performance of radars. The intermittent sampling and forwarding jammer using digital radio frequency memory (DRFM) technology can sample and repeatedly forward part of the radar transmission signal, forming a multi-false target or dense false target interference effect at the radar receiving end. It has the characteristics of flexible use, strong adaptability and high threat, and has become one of the mainstream methods of radar jamming technology.

[0003] With the development of intermittent sampling forwarding jamming technology, many scholars at home and abroad have conducted extensive research on interference identification and suppression methods in the spatial domain, waveform domain, and time-frequency domain. In the spatial domain, multi-channel array adaptive beamforming technology can be used to suppress sidelobe interference, but when the jammer is located in the main lobe of the radar transmit beam, while suppressing interference in the spatial domain, it will also cause serious loss of target energy. In the waveform domain, intermittent sampling forwarding interference can be effectively suppressed by designing intra-pulse orthogonal waveforms, Doppler-sensitive waveforms, mismatch filters, etc., but such methods require solving complex waveform optimization problems and are difficult to apply in real time to rapidly changing interference scenarios. There are two main methods for identifying and suppressing intermittent sampling forwarding interference in the time-frequency domain: one is to estimate the time-frequency parameters from the time-frequency diagram, identify and reconstruct the interference, and then perform interference suppression by subtracting the radar received signal; the other is to directly construct a time-frequency domain bandpass filter based on the time-frequency diagram to suppress interference. However, both types of time-frequency domain interference identification and suppression methods require short-time Fourier transform to obtain the time-frequency diagram. The short-time Fourier transform reduces the time domain resolution in the time domain sliding window. For the first type of method, it will reduce the accuracy of parameter estimation and affect the reconstruction and suppression of interference signals; for the second type of method, it will lose interference-free samples and affect the construction of the bandpass filter. In addition, the time-frequency analysis is highly complex and requires a large storage space, which has high hardware requirements for the radar system. Summary of the invention

[0004] In view of this, the present invention provides a method for identifying and suppressing intermittent sampling and forwarding interference based on differential features, which can effectively realize target detection in intermittent sampling and forwarding interference scenarios.

[0005] The technical solution for implementing the present invention is as follows:

[0006] The intermittent sampling forwarding interference identification and suppression method based on differential features includes: extracting the differential features of radar receiving signals; comparing the result of the first-order differential features after passing through a square law detector with a threshold γ for conventional detection to obtain an alternative signal source; using the difference between the target echo and the interference signal in the differential feature space to perform interference identification on the alternative signal source; and outputting the target detection result.

[0007] Furthermore, the extraction of the differential features of the radar received signal is specifically as follows:

[0008] The radar transmission signal is recorded as s0(t), and the radar reception signal is recorded as s(t). s(t) contains the target echo, interference signal and environmental noise, and t is the time axis. The Mth (M=1, 2, ..., M) of the radar reception signal is extracted by the following formula: max )-order differential feature x M (t):

[0009]

[0010] Where T p is the pulse width of the radar transmission signal; u is the integral variable; is the impulse response function of the matched filter, the superscript * indicates conjugate; w M (u) is the Mth order difference window function, which takes the length of T p The integral interval is divided into M equal parts, and the value of each part is recorded as c M (m), m = 0, ..., M-1; so the difference window function w M (u) can be expressed as

[0011]

[0012] Among them, T c =T p / M,rect(· / T c ) indicates that the window length is T c Rectangular window function of M (m) is given by the following difference sequence

[0013]

[0014] After normalization, we get

[0015]

[0016]

[0017] In particular, when M = 1

[0018]

[0019] It can be seen that the first-order differential feature x1(t) is the result of matched filtering; the coefficient c M (m) satisfies when M>1

[0020]

[0021] Furthermore, the conventional detection is specifically:

[0022] The first-order differential feature (i.e., the matched filtering result) x1(t) is passed through the square law detector and compared with the threshold γ for conventional detection. The decision criterion is as follows:

[0023]

[0024] Where r1(t) represents the decision result of the square-law detector; the threshold γ is determined by |x1(t)| when only noise exists. 2 The probability density function of is determined by the false alarm probability of conventional radar;

[0025] If in t n , n = 1, 2, ..., N times satisfy

[0026] r1(t n )=1, n=1, 2,..., N (9)

[0027] This means that at t n , n=1, 2, ..., there may be a target or interference at N moments.

[0028] Furthermore, the interference identification is specifically:

[0029] Using the difference between the target echo and the interference signal in the differential feature space, t n , n=1, 2, ..., N time instant alternative signal sources are used for interference identification, and the identification criteria are as follows:

[0030]

[0031] Among them, r2(t) represents the interference and target identification results; R(t n ) is constructed as the first-order differential feature and other second to M max The ratio of the energy accumulation results of the order difference characteristics is shown in the following formula:

[0032]

[0033] The identification threshold ∈ is determined by the different distributions of the differential characteristic energy ratios between the target and the interference according to the minimum error probability criterion.

[0034] Furthermore, the output target detection result is specifically:

[0035] If in t n , n = 1, 2, ..., there is a time t in N i , i∈[1,2,...,N] satisfies r2(t i )=1, it is determined that there is a target in the radar received signal; otherwise, it is determined that there is no target in the radar received signal.

[0036] Beneficial effects:

[0037] 1. The present invention utilizes the difference between the target echo and the intermittent sampling forwarding interference signal in the differential feature space to realize target detection while identifying and suppressing interference, and does not require complex optimization operations and time-frequency analysis. The algorithm complexity is low and is suitable for engineering practice.

[0038] 2. The present invention proposes a new signal differential feature extraction method. By adding a "differential window" in the pulse compression process, the responses of the target and the interference (i.e., the differential features) show obvious differences with lower computational complexity, which provides the possibility for subsequent interference identification.

[0039] 3. The present invention designs an interference identification criterion by utilizing the difference between the differential features of the target echo and the interference signal, and takes the ratio of the differential feature energy as a statistic, which further amplifies the difference between the target and the interference in the differential space. It obtains a larger value at the target and a relatively smaller value at the interference, which can effectively realize the identification and suppression of interference. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 The flowchart of the intermittent sampling forwarding interference identification and suppression method based on differential characteristics.

[0041] Figure 2 The probability density distribution of the differential characteristic energy ratio at the target under different signal-to-noise ratios and at the interference under different interference-to-noise ratios. (1) is the probability density distribution of the differential characteristic energy ratio at the target under different signal-to-noise ratios, and (2) is the probability density distribution of the differential characteristic energy ratio at the interference under different interference-to-noise ratios.

[0042] Figure 3 The 1-6 order differential features of the target and interference in the simulation example. (1) is the 1-6 order differential features of the target, and (2) is the 1-6 order differential features of the interference.

[0043] Figure 4 It is the routine detection process in the simulation example. (1) is the routine detection input, and (2) is the routine detection result.

[0044] Figure 5 This is the interference identification process in the simulation example. (1) is the interference identification input, and (2) is the interference identification result. DETAILED DESCRIPTION

[0045] The present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0046] The present invention provides a method for identifying and suppressing intermittent sampling forwarding interference based on differential characteristics, such as Figure 1 As shown, the specific steps include:

[0047] Step 1: Differential feature extraction.

[0048] Assume that the radar transmission signal is a rectangular envelope linear frequency modulation signal, record the radar transmission signal as s0(t), and the radar reception signal as s(t), where s(t) contains the target echo, interference signal, and environmental noise, and t is the time axis. The Mth radar reception signal is extracted by the following formula, where M = 1, 2, ..., M max Order difference feature x M (t):

[0049]

[0050] Where T p is the pulse width of the radar transmission signal; u is the integral variable; is the impulse response function of the matched filter, the superscript * indicates conjugate; w M (u) is the Mth order difference window function, which takes the length of T p The integral interval is divided into M equal parts, and the value of each part is recorded as c M (m), m = 0, ..., M-1. So the difference window function w M (u) can be expressed as

[0051]

[0052] Among them, T c =T p / M,rect(· / T c ) indicates that the window length is T c The coefficients c of each item are M (m) is given by the following difference sequence

[0053]

[0054] After normalization, we get

[0055]

[0056]

[0057] In particular, when M = 1

[0058]

[0059] It can be seen that the first-order differential feature x1(t) is the result of matched filtering. M (m) satisfies when M>1

[0060]

[0061] Therefore, for the target echo, in addition to the matched filtering result x1(t), other differential features x1(t) obtained by formula (1) are used. M (t), M≠1, there is a notch at the target position with a lower amplitude than that at the nearby position; however, this phenomenon does not exist for interference, and the target echo and interference signal show significant differences in the differential feature space.

[0062] Step 2: Routine testing.

[0063] The first-order differential feature (i.e., the matched filtering result) x1(t) is passed through the square law detector and compared with the threshold γ for conventional detection. The decision criterion is as follows:

[0064]

[0065] Where r1(t) represents the decision result of the square law detector. The threshold γ is determined by |x1(t)| when only noise exists. 2 The probability density function of the radar is determined by the false alarm probability of the conventional radar.

[0066] If in t n , n = 1, 2, ..., N times satisfy

[0067] r1(t n )=1, n=1, 2,..., N (9)

[0068] This means that at t n , n=1, 2, ..., there may be a target or interference at N moments.

[0069] Step 3: Interference identification.

[0070] Using the difference between the target echo and the interference signal in the differential feature space, t n , n=1, 2, ..., N time instant alternative signal sources are used for interference identification, and the identification criteria are as follows:

[0071]

[0072] Among them, r2(t) represents the interference and target identification results; R(t n ) is constructed as the first-order differential feature and other second to M max The ratio of the energy accumulation results of the order difference characteristics is shown in the following formula:

[0073]

[0074] The identification threshold ∈ can be determined according to the minimum error probability criterion by the different distributions of the differential characteristic energy ratios at the target and interference. The differential characteristic energy ratio constructed by formula (11) appears larger at the target, while the response at the interference is relatively small, that is, it has an inhibitory effect on the interference. Its distribution is as follows: Figure 2 As shown. Among them, Figure 2 (1) is the probability density distribution of the differential feature energy ratio at the target under different signal-to-noise ratios, Figure 2 (2) is the probability density distribution of the differential characteristic energy ratio at the interference point under different interference-to-noise ratios.

[0075] Step 4: Output target detection results.

[0076] If in t n , n = 1, 2, ..., there is a time t in N i , i∈[1,2,...,N] satisfies r2(t i )=1, it is determined that there is a target in the radar received signal; otherwise, it is determined that there is no target in the radar received signal.

[0077] A simulation example of applying the present invention is given below, and its specific process is explained.

[0078] Consider the following simulation scenario: there is a target and a set of interference (intercepting the first 1 / 6 of the transmitted signal and repeating it 5 times) in the radar receiving signal, and the noise is complex Gaussian white noise. The source waveform parameters are set as follows:

[0079]

[0080] The simulation parameters are set as follows:

[0081]

[0082] Step 1: Differential feature extraction.

[0083] Set the coefficients of the 1-6 order difference window function to:

[0084]

[0085] The 1-6 order differential features x1(t), x2(t), ..., x6(t) are extracted from formula (1). The 1-6 order differential features of the target and interference are as follows: Figure 3 As shown. Among them, Figure 3 (1) is the 1-6 order differential feature at the target, Figure 3 (2) is the 1st to 6th order differential characteristics at the interference point.

[0086] Step 2: Routine testing.

[0087] Compare x1(t) with the conventional detection threshold γ through the square law detector to obtain the conventional detection result, such as Figure 4 As shown. Among them, Figure 4 (1) is the input of conventional detection, i.e. x1(t) and the conventional detection threshold γ; Figure 4 (2) is the conventional detection result. It can be seen that both the target and the interference can pass the conventional detection threshold and be judged as candidate sources.

[0088] Step 3: Interference identification.

[0089] The differential characteristic energy ratio of the candidate signal source is calculated by formula (11) and compared with the identification threshold ∈ to obtain the target and interference identification results, as follows: Figure 5 As shown. Among them, Figure 5 (1) is the input of the interference identification step, namely, the differential characteristic energy ratio of the candidate signal source and the identification threshold ∈; Figure 5 (2) is the interference recognition result. It can be seen that the interference recognition rate is 100% and the target can also be identified.

[0090] Step 4: Output target detection results.

[0091] Depend on Figure 5 From the identification result (2), it can be seen that the candidate signal source at 26 km is identified as the target. Output the detection result that there is a target at 26 km.

[0092] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for identifying and suppressing intermittent sampling and forwarding interference based on differential features, characterized in that: include: Extract differential features of radar received signals; The result of the first-order differential feature after passing through the square law detector is compared with the threshold γ for conventional detection to obtain the candidate signal source; the difference between the target echo and the interference signal in the differential feature space is used to perform interference identification on the candidate signal source; and the target detection result is output; The interference identification is specifically as follows: Using the difference between the target echo and the interference signal in the differential feature space, t n ,n=1,2,…,N time instant alternative signal sources are used for interference identification, and the identification criteria are as follows: Among them, r2(t n ) represents the interference and target identification results; R(t n ) is constructed as the first-order differential feature and other second to M max The ratio of the energy accumulation results of the order difference characteristics is shown in the following formula: The identification threshold ∈ is determined by the different distributions of the differential characteristic energy ratios between the target and the interference according to the minimum error probability criterion.

2. The method for identifying and suppressing intermittent sampling and forwarding interference based on differential features according to claim 1, characterized in that: The step of extracting the differential features of the radar receiving signal is specifically as follows: The radar transmission signal is recorded as s0(t), and the radar reception signal is recorded as s(t). s(t) contains the target echo, interference signal and environmental noise, and t is the time axis. The Mth (M=1,2,…,Mth) of the radar reception signal is extracted by the following formula: max )-order differential feature x M (t): Among them, T p is the pulse width of the radar transmission signal; u is the integral variable; is the impulse response function of the matched filter, the superscript * indicates conjugate; w M (u) is the Mth order difference window function, which takes the length of T p The integral interval is divided into M equal parts, and the value of each part is recorded as c M (m), m = 0, ..., M-1; so the difference window function w M (u) can be expressed as Among them, T c =T p / M,rect(· / T c ) indicates that the window length is T c Rectangular window function of M (m) is given by the following difference sequence After normalization, we get In particular, when M = 1 The first-order differential feature x1(t) is the result of matched filtering; the coefficient c M (m) satisfies when M>1 3. The method for identifying and suppressing intermittent sampling and forwarding interference based on differential features according to claim 1 or 2, characterized in that: The conventional detection is specifically: The result of passing the first-order differential feature x1(t) through the square law detector is compared with the threshold γ for conventional detection. The decision criterion is as follows: Where r1(t) represents the decision result of the square-law detector; the threshold γ is determined by |x1(t)| when only noise exists. 2 The probability density function of is determined by the false alarm probability of conventional radar; If in t n ,n=1,2,…,N satisfies at any moment r1(t n )=1,n=1,2,…,N(9) This means that at t n ,n=1,2,…,there may be targets or interferences at N moments.

4. The method for identifying and suppressing intermittent sampling and forwarding interference based on differential features according to claim 1, characterized in that: The output target detection result is specifically: If in t n ,n=1,2,…,N exists at time t i ,i∈[1,2,…,N] satisfies r2(t i )=1, it is determined that there is a target in the radar received signal; otherwise, it is determined that there is no target in the radar received signal.

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