An adaptive bearing update method for radar signal sorting

Abstract

This application provides an adaptive azimuth update method for radar signal sorting, relating to the field of electronic warfare radar reconnaissance signal processing technology. The method includes: Step 1, a temporary result azimuth feature statistics module statistically analyzes the parameter characteristics of all pulses and the azimuth characteristics of large-amplitude pulses in each radar pulse sequence, outputting a single-frame temporary result for each signal. Step 2, a large-amplitude signal identification judgment module performs large-amplitude signal identification judgment based on the target scanning type and target amplitude information. Step 3, an adaptive azimuth update processing module, based on the large-amplitude signal identification judgment result, adaptively updates the azimuth of the target signal for three states: tracking signal, non-tracking large-amplitude signal, and non-tracking small-amplitude signal. This invention achieves adaptive azimuth update processing for radar signal sorting by addressing changes in the target scanning type and detection amplitude information of the radiation source, improving the statistical accuracy of the output azimuth of the signal sorting.

Description

Technical Field

[0001] This application relates to the field of electronic warfare radar reconnaissance signal processing technology, and in particular to an adaptive azimuth update method for radar signal sorting. Background Technology

[0002] Radar signal sorting is a crucial part of radar reconnaissance systems. First, the system receives the interleaved pulse descriptor (PDW) data stream measured by the receiver. Through clustering and deinterleaving processing, the pulse sequences corresponding to each radar radiation source are separated sequentially. A single-frame temporary result is obtained through parameter feature statistics. Then, the single-frame temporary result is fused with the target table information to output a long-term stable radiation source descriptor (EDW).

[0003] During the provisional result parameter feature statistics, the source parameter feature statistics for each extracted radar radiation source are performed on all pulse sequences in a single frame, including carrier frequency, multiple cycles, amplitude, azimuth, etc. During target table parameter fusion processing, the provisional result information is used to update the parameters of the fused target information.

[0004] In existing signal sorting methods, the azimuth update for each radar source is performed using all extracted pulse sequences, without differentiated processing for changes in target scanning type and amplitude information. For tracking radars, with a large number of pulses and small amplitude fluctuations, the azimuth statistics obtained by this method can be directly output. However, for search radars, when the radar reconnaissance system simultaneously detects both the main lobe and sidelobes, and the sidelobes are near the receiver sensitivity, the azimuth measurement error of the sidelobes increases. This causes fluctuations in the azimuth update value in the output EDW due to the switching between the main lobe and sidelobes. Summary of the Invention

[0005] This application provides an adaptive azimuth update method for radar signal sorting, which can be used to solve the technical problem of low statistical accuracy of the output azimuth of current signal sorting.

[0006] This application provides an adaptive azimuth update method for radar signal sorting, the method comprising:

[0007] Step 1: The temporary result azimuth feature statistics module receives the interleaved PDW data stream measured by the receiver. Through clustering and deinterleaving processing, it sequentially separates the pulse sequences corresponding to each radar radiation source, performs parameter feature statistics of all pulses in a single frame of each radar pulse sequence and azimuth feature statistics of large amplitude pulses, and outputs the temporary results of each signal in a single frame.

[0008] Step 2: The large amplitude signal identification judgment module receives the temporary results of each signal single frame from the temporary result azimuth feature statistics module, finds the matching target table batch number through parameter fusion processing, and makes a large amplitude signal identification judgment based on the scanning type and target amplitude information.

[0009] Step 3: Based on the large amplitude signal identification result, the adaptive azimuth update processing module performs adaptive update processing on the azimuth of the target signal for three states: tracking signal, non-tracking large amplitude signal, and non-tracking small amplitude signal.

[0010] Further, in step 1, the temporary result azimuth feature statistics module receives the interleaved PDW data stream measured by the receiver, and through clustering and deinterleaving processing, sequentially separates the pulse sequences corresponding to each radar radiation source, performs parameter feature statistics for all pulses in a single frame of each radar pulse sequence and azimuth feature statistics for large amplitude pulses, and outputs the temporary results for each signal frame, including:

[0011] Step 101, the i-th frame interleaved PDW data stream PDWi measured by the receiver is:

[0012]

[0013] Where J represents the total number of pulses in the i-th frame. This represents the amplitude value of the j-th pulse in the i-th frame. This represents the azimuth value of the j-th pulse in the i-th frame. Other parameter values ​​representing the j-th pulse in the i-th frame include carrier frequency, arrival time, and pulse width. Through clustering and deinterlacing, the pulse sequences corresponding to each radar radiation source are sequentially separated. in K m This represents the total number of pulses per frame for the m-th radiation source in the i-th frame.

[0014] Step 102: Calculate the parameter characteristic statistics of all pulses in a single frame of the pulse sequence of the same radiation source. Where m∈[1,M], This represents the single-frame carrier frequency, multiple cycles, and pulse width of the m-th radiation source; This represents the maximum amplitude of the m-th radiation source in a single frame; This represents the average of all pulse orientations in a single frame from the m-th radiation source;

[0015] Step 103: Calculate the azimuth characteristic statistics of large-amplitude pulses in the pulse sequence of the same radiation source. and effective orientation markings

[0016] Step 104: Output the temporary single-frame results for each radiation source. in

[0017]

[0018] Further, in step 103, the azimuth characteristic statistics of large-amplitude pulses in the pulse sequence of the same radiation source are calculated.

[0019] and effective orientation markings include:

[0020] Step 1031, initialize the amplitude threshold thd P a, minimum number of pulses processed (thdpn); if Pa m ≥thd Pa Proceed to step 1032; otherwise, proceed to step 1034.

[0021] Step 1032: The current radiation source is a large-amplitude signal; extract pulses with amplitudes greater than the amplitude threshold. in K' is the total number of pulses greater than the amplitude threshold;

[0022] Step 1033, if the total number of pulses K' greater than the amplitude threshold ≥ thd pn ,but Proceed to step 104; otherwise, proceed to step 1034.

[0023] Step 1034: The current radiation source is a small-amplitude signal; therefore, no azimuth feature statistics are performed for large-amplitude pulses. Valid azimuth identification is established. Statistical values ​​of azimuth characteristics of large amplitude pulses

[0024] Further, in step 2, the large-amplitude signal identification module receives the temporary results of each signal frame from the temporary result azimuth feature statistics module, finds the matching target table batch number through parameter fusion processing, and performs large-amplitude signal identification based on the scan type and target amplitude information; including:

[0025] Step 201, set the target table batch number information list before processing the current frame to... in Let i be the target parameters of the nth target at time i-1. Let be the amplitude value of the nth target at time i-1. Let be the azimuth value of the nth target at time i-1. For the other parameter values ​​of the nth target at time i-1, including carrier frequency, frequency repetition, and pulse width, The scan type for the nth target at time i-1; scan types include tracking and non-tracking; non-tracking includes scanning and unknown.

[0026] Step 202: Receive the temporary results of each signal frame from the temporary result azimuth feature statistics module, perform parameter fusion processing using carrier frequency, frequency repetition, and pulse width, find the matching target batch number, and let... and Matching, and then updating parameters

[0027]

[0028] Step 203, if the scan type To proceed with the investigation, proceed to step 204; otherwise, proceed to step 205.

[0029] Step 204: The current target is the tracking target; large amplitude signal processing (i.e., large amplitude signal identification) is not enabled. Perform step 3;

[0030] Step 205, the current target is a non-tracking target, if Then, large amplitude signal processing, i.e., large amplitude signal identification, is enabled. Otherwise, large amplitude signal processing, i.e., large amplitude signal flagging, will not be enabled.

[0031] Further, in step 3, the adaptive azimuth update processing module, based on the large amplitude signal identification result, adaptively updates the azimuth of the target signal for three states: tracking signal, non-tracking large amplitude signal, and non-tracking small amplitude signal. This includes:

[0032] Step 301: Iterate through the target table. If there is no matching temporary result for the target batch number in the current frame, the orientation is not updated. Execute step 306;

[0033] Step 302, if a large signal is indicated If the value is 0, proceed to step 303; if the signal is large... If the result is 1, proceed to step 304; otherwise, proceed to step 305.

[0034] Step 303, tracking signal azimuth update processing, azimuth is updated directly, that is... Execute step 306;

[0035] Step 304, Non-tracking large-amplitude signal azimuth update processing: The current target is non-tracking and large-amplitude signal processing is currently enabled. If the azimuth of the temporary result is valid... If the value is 0, the orientation will not be updated. If the location identifier of the provisional result is valid If the value is 1, then the orientation is updated. Execute step 306;

[0036] Step 305, Non-tracking small-amplitude signal azimuth update processing: The current target is non-tracking and large-amplitude signal processing is not currently enabled. If the azimuth of the temporary result is valid... If it is 0, then If the location identifier of the provisional result is valid If it is 1, then Execute step 306;

[0037] Step 306, Output target batch number information

[0038] Compared with existing methods that use all pulse sequences of each radar radiation source for azimuth statistics and updates in signal sorting, this application comprehensively considers the changes in azimuth measurement error caused by changes in radiation source target scanning type and detection amplitude information, and divides the azimuth update processing into tracking signals, non-tracking large amplitude signals, and non-tracking small amplitude signals, thus realizing adaptive azimuth update processing for radar signal sorting.

[0039] This application addresses the situation where a radar reconnaissance system simultaneously detects both the main lobe and sidelobe of a search-mode radar. It employs a non-tracking large-amplitude signal update processing method, utilizing the azimuth characteristic statistical values ​​of large-amplitude pulses for azimuth update, thereby improving the statistical accuracy of the signal sorting output azimuth. Attached Figure Description

[0040] Figure 1 A flowchart of the azimuth adaptive update method for radar signal sorting provided in the embodiments of this application;

[0041] Figure 2 Interleaved PDW data streams measured by the receiver provided in the embodiments of this application;

[0042] Figure 3 A statistical diagram of the azimuth characteristics of the tracking signal provided in the embodiments of this application;

[0043] Figure 4 This application provides a statistical chart of the azimuth characteristics of a non-tracking large-amplitude signal in an embodiment.

[0044] Figure 5 A statistical chart of the azimuth characteristics of a non-tracking small-amplitude signal provided in an embodiment of this application. Detailed Implementation

[0045] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of the present invention.

[0046] Reference Figure 1 As shown, the adaptive azimuth update method for radar signal sorting provided in this embodiment of the invention includes the following steps:

[0047] Step 1: The temporary result azimuth feature statistics module receives the interleaved PDW data stream measured by the receiver. Through clustering and deinterleaving processing, it sequentially separates the pulse sequences corresponding to each radar radiation source, performs parameter feature statistics of all pulses in a single frame of each radar pulse sequence and azimuth feature statistics of large amplitude pulses, and outputs the temporary results of each signal in a single frame.

[0048] Step 2: The large amplitude signal identification judgment module receives the temporary results of each signal single frame from the temporary result azimuth feature statistics module, finds the matching target table batch number through parameter fusion processing, and makes a large amplitude signal identification judgment based on the scanning type and target amplitude information.

[0049] Step 3: Based on the large amplitude signal identification result, the adaptive azimuth update processing module performs adaptive update processing on the azimuth of the target signal for three states: tracking signal, non-tracking large amplitude signal, and non-tracking small amplitude signal.

[0050] Optionally, in some possible implementations, step 1 specifically includes:

[0051] Step 1.1 Receive the i-th frame interleaved pulse descriptor (PDW) data stream measured by the receiver. Where J represents the total number of pulses in the i-th frame. This represents the amplitude value of the j-th pulse in the i-th frame. This represents the azimuth value of the j-th pulse in the i-th frame. Other parameter values ​​(carrier frequency, arrival time, pulse width, etc.) of the j-th pulse in the i-th frame are used to sequentially separate the pulse sequences corresponding to each radar radiation source through clustering and deinterleaving processing. in K m This represents the total number of pulses per frame for the m-th radiation source in the i-th frame.

[0052] Multi-frame interleaved PDW data streams, such as Figure 2 As shown, the PDW data stream includes range, amplitude, radio frequency, and pulse width. After processing multiple frames in 500ms increments, the separated radar radiation source pulses in each frame contain tracking signals, such as... Figure 3 As shown, non-tracking large signals, such as Figure 4 As shown, non-tracking small signals, such as Figure 5 As shown.

[0053] Step 1.2 Calculate the parameter characteristic statistics of all pulses in a single frame of the pulse sequence of the same radiation source. Where m∈[1,M], This represents the statistical characteristics of the single-frame carrier frequency, multiple cycles, pulse width, etc., of the m-th radiation source; This represents the maximum amplitude of the m-th radiation source in a single frame; This represents the average of all pulse orientations in a single frame from the m-th radiation source.

[0054] make for Figure 3 The corresponding target batch number information, for Figure 4 The corresponding target batch number information, for Figure 5 The corresponding target batch number information. Figures 3-5 Statistical values ​​of azimuth characteristics of all pulses As shown in Table 1. Figures 3 to 5 (a) are all Doa feature statistics charts; (b) are all DoaBig feature statistics charts; each column corresponds to the value of i from 1 to 6.

[0055] Table 1. Statistical values ​​of azimuth characteristics of all pulses in the provisional results.

[0056]

[0057] Step 1.3 Calculate the azimuth characteristic statistics of large-amplitude pulses in the pulse sequence of the same radiation source. and effective orientation markings

[0058] Step 1.3.1 Initialize the amplitude threshold thd Pa =10, minimum number of pulses processed (thd) pn =5. If Pa m ≥thd Pa If the condition is met, proceed to step 1.3.2; otherwise, proceed to step 1.3.4.

[0059] Step 1.3.2: Since the current radiation source is a large-amplitude signal, extract pulses with amplitudes greater than the amplitude threshold. in K' is the total number of pulses greater than the amplitude threshold.

[0060] Step 1.3.3 If the total number of pulses K' greater than the amplitude threshold is ≥ thd pn ,but Proceed to step 1.4; otherwise, proceed to step 1.3.4.

[0061] Step 1.3.4 Since the current radiation source is a small-amplitude signal, no azimuth feature statistics are performed for large-amplitude pulses, i.e., the azimuth is effectively identified. Statistical values ​​of azimuth characteristics of large amplitude pulses

[0062] Figures 3-5 Statistical values ​​of the azimuth characteristics of large amplitude pulses As shown in Table 2, the effective azimuth indicators of large-amplitude pulses As shown in Table 3.

[0063] Table 2. Statistical values ​​of azimuth characteristics of large-amplitude pulses in temporary results.

[0064]

[0065] Table 3. Temporary Results: Effective Identifiers of the Location of Large-Amplitude Pulses

[0066]

[0067] Step 1.4 Output the temporary single-frame results for each radiation source. in

[0068]

[0069] Optionally, in some possible implementations, step 2 specifically includes:

[0070] Step 2.1 Before processing the current frame, the target table batch number information list is as follows: in For the target parameters of the nth target, Let be the amplitude value of the nth target at time i-1. Let be the azimuth value of the nth target at time i-1. For the other parameter values ​​(carrier frequency, arrival time, pulse width, etc.) of the nth target at time i-1, The scan type (tracking, scanning, unknown, etc.) of the nth target at time i-1.

[0071] Step 2.2 Receive the temporary results of each signal frame from the temporary result azimuth feature statistics module, find the matching target table batch number through parameter fusion processing, and let... and Matching, and then updating parameters

[0072] Step 2.3 If the scan type If you want to track it, proceed to step 2.4; otherwise, proceed to step 2.5.

[0073] Step 2.4 The current target is the tracking target; large amplitude signal processing (i.e., large amplitude signal identification) is not enabled. Proceed to step 3.

[0074] Step 2.5 The current target is a non-tracking target, if Then, large amplitude signal processing, i.e., large amplitude signal identification, is enabled. Otherwise, large amplitude signal processing, i.e., large amplitude signal flagging, will not be enabled.

[0075] make for Figure 3 The corresponding target batch number information, for Figure 4 The corresponding target batch number information, for Figure 5 The corresponding target batch number information. Figures 3-5 large signal indicators As shown in Table 4.

[0076] Table 4 Target Table Large Amplitude Signal Indicators

[0077]

[0078] Optionally, in some possible implementations, step 3 specifically includes:

[0079] Step 3.1 Iterate through the target table. If there is no matching temporary result for the target batch number in the current frame, the orientation is not updated. Proceed to step 3.6.

[0080] Step 3.2 If a large signal is indicated If the value is 0, proceed to step 3.3; if the signal is large... If the result is 1, proceed to step 3.4; otherwise, proceed to step 3.5.

[0081] Step 3.3 Tracking signal azimuth update processing: The azimuth is updated directly, i.e. Proceed to step 3.6.

[0082] Step 3.4 Non-tracking large-amplitude signal azimuth update processing: The current target is non-tracking and large-amplitude signal processing is currently enabled. If the azimuth of the temporary result is valid... If the value is 0, the orientation will not be updated. If the location identifier of the provisional result is valid If the value is 1, then the orientation is updated. Proceed to step 3.6.

[0083] Step 3.5 Non-tracking small-amplitude signal azimuth update processing: The current target is non-tracking and large-amplitude signal processing is not currently enabled. If the azimuth of the temporary result is valid... If it is 0, then If the location identifier of the provisional result is valid If the value is 1, then the orientation is updated. Proceed to step 3.6.

[0084] Step 3.6 Output target batch number information

[0085] Figures 3-5 Target signal orientation As shown in Table 5.

[0086] Table 5 Target Table Signal Location

[0087]

[0088]

[0089] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An adaptive azimuth update method for radar signal sorting, characterized in that, The method includes: Step 1: The temporary result azimuth feature statistics module receives the interleaved PDW data stream measured by the receiver. Through clustering and deinterleaving processing, it sequentially separates the pulse sequences corresponding to each radar radiation source, performs parameter feature statistics of all pulses in a single frame of each radar pulse sequence and azimuth feature statistics of large amplitude pulses, and outputs the temporary results of each signal in a single frame. Step 2: The large amplitude signal identification judgment module receives the temporary results of each signal single frame from the temporary result azimuth feature statistics module, finds the matching target table batch number through parameter fusion processing, and makes a large amplitude signal identification judgment based on the scanning type and target amplitude information. Step 3: Based on the large amplitude signal identification result, the adaptive azimuth update processing module performs adaptive update processing on the azimuth of the target signal for three states: tracking signal, non-tracking large amplitude signal, and non-tracking small amplitude signal.

2. The adaptive azimuth update method for radar signal sorting according to claim 1, characterized in that, Step 1: The temporary result azimuth feature statistics module receives the interleaved PDW data stream measured by the receiver. Through clustering and deinterleaving processing, it sequentially separates the pulse sequences corresponding to each radar radiation source, performs parameter feature statistics for all pulses in a single frame of each radar pulse sequence, and performs azimuth feature statistics for large-amplitude pulses. It then outputs the temporary results for each signal frame, including: Step 101, the i-th frame interleaved PDW data stream PDWi measured by the receiver is: Where J represents the total number of pulses in the i-th frame. This represents the amplitude value of the j-th pulse in the i-th frame. This represents the azimuth value of the j-th pulse in the i-th frame. Other parameter values ​​representing the j-th pulse in the i-th frame include carrier frequency, arrival time, and pulse width. Through clustering and deinterlacing, the pulse sequences corresponding to each radar radiation source are sequentially separated. in K m This represents the total number of pulses per frame for the m-th radiation source in the i-th frame. Step 102: Calculate the parameter characteristic statistics of all pulses in a single frame of the pulse sequence of the same radiation source. Where m∈[1,M], This represents the single-frame carrier frequency, multiple cycles, and pulse width of the m-th radiation source; This represents the maximum amplitude of the m-th radiation source in a single frame; This represents the average of all pulse orientations in a single frame from the m-th radiation source; Step 103: Calculate the azimuth characteristic statistics of large-amplitude pulses in the pulse sequence of the same radiation source. and effective orientation markings Step 104: Output the temporary single-frame results for each radiation source. in 3. The adaptive azimuth update method for radar signal sorting according to claim 2, characterized in that, Step 103: Calculate the azimuth characteristic statistics of large-amplitude pulses in the pulse sequence of the same radiation source. and effective orientation markings include: Step 1031, initialize the amplitude threshold thd Pa Minimum number of pulses processed (thd) pn If Pa m ≥thd Pa Proceed to step 1032; otherwise, proceed to step 1034. Step 1032: The current radiation source is a large-amplitude signal; extract pulses with amplitudes greater than the amplitude threshold. in K' is the total number of pulses greater than the amplitude threshold; Step 1033, if the total number of pulses K' greater than the amplitude threshold ≥ thd pn ,but Proceed to step 104; otherwise, proceed to step 1034. Step 1034: The current radiation source is a small-amplitude signal; azimuth valid identification. Statistical values ​​of azimuth characteristics of large amplitude pulses 4. The adaptive azimuth update method for radar signal sorting according to claim 1, characterized in that, Step 2: The large amplitude signal identification judgment module receives the temporary results of each signal single frame from the temporary result azimuth feature statistics module, finds the matching target table batch number through parameter fusion processing, and makes a large amplitude signal identification judgment based on the scanning type and target amplitude information. include: Step 201, set the target table batch number information list before processing the current frame to... in Let i be the target parameters of the nth target at time i-1. Let be the amplitude value of the nth target at time i-1. Let be the azimuth value of the nth target at time i-1. For the other parameter values ​​of the nth target at time i-1, including carrier frequency, frequency repetition, and pulse width, The scan type for the nth target at time i-1; scan types include tracking and non-tracking; non-tracking includes scanning and unknown. Step 202: Receive the temporary results of each signal frame from the temporary result azimuth feature statistics module, perform parameter fusion processing using carrier frequency, frequency repetition, and pulse width, find the matching target batch number, and let... and Matching, and then updating parameters Step 203, if the scan type To proceed with the investigation, proceed to step 204; otherwise, proceed to step 205. Step 204: The current target is the tracking target; large amplitude signal processing (i.e., large amplitude signal identification) is not enabled. Perform step 3; Step 205, the current target is a non-tracking target, if Then, large amplitude signal processing, i.e., large amplitude signal identification, is enabled. Otherwise, large amplitude signal processing, i.e., large amplitude signal flagging, will not be enabled.

5. The adaptive azimuth update method for radar signal sorting according to claim 1, characterized in that, Step 3: The adaptive azimuth update processing module, based on the large amplitude signal identification result, adaptively updates the azimuth of the target signal for three states: tracking signal, non-tracking large amplitude signal, and non-tracking small amplitude signal. This includes: Step 301: Iterate through the target table. If there is no matching temporary result for the target batch number in the current frame, the orientation is not updated. Execute step 306; Step 302, if a large signal is indicated If the value is 0, proceed to step 303; if the signal is large... If the result is 1, proceed to step 304; otherwise, proceed to step 305. Step 303, tracking signal azimuth update processing, azimuth is updated directly, that is... Execute step 306; Step 304, Non-tracking large-amplitude signal azimuth update processing: The current target is non-tracking and large-amplitude signal processing is currently enabled. If the azimuth of the temporary result is valid... If the value is 0, the orientation will not be updated. If the location identifier of the provisional result is valid If the value is 1, then the orientation is updated. Execute step 306; Step 305, Non-tracking small-amplitude signal azimuth update processing: The current target is non-tracking and large-amplitude signal processing is not currently enabled. If the azimuth of the temporary result is valid... If it is 0, then If the location identifier of the provisional result is valid If it is 1, then Execute step 306; Step 306, Output target batch number information

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