Method and device for identifying and suppressing primary radar asynchronous interference based on multi-dimensional features

Abstract

The present invention relates to the field of primary radar technology and provides a method and device for identifying and suppressing asynchronous interference in a primary radar based on multi-dimensional features. The method comprises: acquiring data, including CPI data and clutter map data; using the clutter map data to determine whether there is asynchronous interference in the fast time dimension of the range unit in the CPI data; performing interference detection in the slow time dimension on the range units with asynchronous interference in the fast time dimension, marking the interference units; and performing asynchronous interference suppression on the marked interference units. The present invention can effectively solve the problem of asynchronous interference in radars, can quickly locate the fast time dimension range unit where the interference occurs, accurately identify the interference, and improve the interference recognition rate and correct recognition rate.

Description

Technical Field

[0001] The present invention relates to the field of primary radar technology, and in particular to a method and device for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features. Background Art

[0002] Primary radar systems, as key detection tools, are widely used in various applications, including target tracking, flight safety, and environmental monitoring. However, with the rapid development and widespread application of radar technology, the utilization of radar spectrum resources has increased year by year. The increasing number of radars of different types and systems operating in the same frequency band has led to an increasing problem of interference between radars in the same frequency band, becoming a significant factor affecting radar performance and system reliability. For example, some low-altitude surveillance radars and weather radars have overlapping frequency bands, and some radar networks have similar frequency bands. When these radars operate simultaneously within a certain range, they can cause co-frequency interference, resulting in a large number of false alarms and hindering accurate target detection and analysis.

[0003] Co-channel interference occurs when electromagnetic waves emitted by one radar enter the receiver of another radar when two nearby radars operate in the same or similar frequency bands. This interference is received by both the main and side lobes of the interfering radar antennas. The closer the distance, the stronger the interference. Interference is generally categorized as continuous wave interference and pulse wave interference based on the waveforms emitted by the interfering radars. Pulse wave interference can be further categorized as co-channel synchronous interference and co-channel asynchronous interference based on the pulse repetition frequency. Co-channel synchronous interference occurs when the pulse repetition frequencies of the two radars are identical or multiples of each other. Currently, synchronous interference is technically unsolvable. Co-channel asynchronous interference occurs when the pulse repetition frequencies of the two radars are not multiples of each other and the difference is greater than a certain value. Currently, the majority of observed co-channel interference is co-channel asynchronous interference. When co-channel synchronous interference occurs, asynchronous interference can be generated by varying the pulse repetition frequency. This characteristic of asynchronous interference can be exploited to develop solutions for identifying and suppressing asynchronous interference.

[0004] The problem of asynchronous co-frequency interference is currently addressed from several perspectives. The transmitter addresses this by changing the transmission frequency and encoding method; the signal processor identifies and suppresses interference through time and frequency domain analysis; and the data processor filters the interference image. For typical radars, addressing co-frequency interference from the signal processor is the most cost-effective and effective solution. Current methods for addressing asynchronous co-frequency interference on the signal processor side generally utilize the amplitude characteristics between adjacent multi-pulses in the time domain for detection. In today's increasingly complex electromagnetic environment, these approaches have the following shortcomings and deficiencies:

[0005] 1. The method has limited applicability: It utilizes the characteristics of adjacent pulse amplitudes and has strict requirements on interference characteristics and radar systems. It can only effectively identify interference under low duty cycle, high power and stable conditions.

[0006] 2. Low asynchronous interference recognition rate: When the interference signal has a high duty cycle, low power, or is superimposed with other background signals, the current method's interference recognition effect will be greatly reduced, and the suppression effect cannot be achieved. The key is to effectively identify and suppress interference under high duty cycle and low power conditions.

[0007] 3. Low utilization of data analysis: The current interference identification and suppression methods do not divide the interference landing area, do not classify the interference features in different environments, and do not fully utilize the multi-dimensional characteristics of the data during identification and suppression.

[0008] 4. Resource optimization is not in-depth enough: The current interference identification and suppression method will identify interference for each distance unit data, and there is no method to quickly locate the fast time distance unit where the interference is located. Excessive interference will greatly affect the processing speed. Summary of the Invention

[0009] The present invention aims to provide a method and device for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features, so as to solve the problem of asynchronous interference caused by signals transmitted by devices in the same or near frequency band during detection by the primary radar at the signal processing end.

[0010] In a first aspect, the present invention provides a method for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features, comprising:

[0011] Acquire data, including CPI data and clutter map data;

[0012] Using the clutter map data, determining whether there is asynchronous interference in the fast time dimension where the range unit in the CPI data is located;

[0013] For distance units with asynchronous interference in the fast time dimension, interference detection in the slow time dimension is performed and the interference units are marked;

[0014] Perform asynchronous interference suppression on the marked interference units.

[0015] In a preferred embodiment, the acquired data includes:

[0016] The CPI data is obtained by performing M pulse sampling of N distance units on the baseband I / Q data; wherein the pulse sampling is a slow time dimension sampling, and the distance sampling corresponding to the distance unit is a fast time dimension sampling;

[0017] The clutter map data is expressed as a 01 matrix, where 0 indicates that the distance unit is a clean area, and 1 indicates that the distance unit is a static clutter area.

[0018] In a preferred embodiment, the determining whether there is asynchronous interference in the fast time dimension where the range unit in the CPI data is located by using the clutter map data includes:

[0019] The baseband I / Q data in the CPI data is judged by the 01 matrix of the clutter map data:

[0020] When the clutter map data corresponding to the distance unit is 0, the spectral flatness factor of the distance unit is calculated. When the spectral flatness factor is greater than the spectral flatness threshold, it is determined that asynchronous interference exists in the fast time dimension where the distance unit is located;

[0021] When the clutter map data corresponding to the range unit is 1, the clutter phase alignment factor of the range unit is calculated. When the clutter phase alignment factor is greater than the clutter phase alignment threshold, it is determined that asynchronous interference exists in the fast time dimension where the range unit is located.

[0022] In a preferred embodiment, the method for calculating the spectral flatness factor includes:

[0023] The spectral components of the discrete signal of the baseband I / Q data are sorted from low value to high value, some of the lowest values ​​are removed from the sorted spectral components, and the inverse of the standard deviation of the remaining spectral components is calculated to obtain the spectral flatness factor; the spectral components are obtained by Fourier transforming the discrete signal of the baseband I / Q data.

[0024] In a preferred embodiment, the method for calculating the clutter phase alignment factor includes:

[0025]

[0026] in, represents the clutter phase alignment factor, Baseband I / Q data is n Discrete signal of discrete points, m is the number of discrete points of the discrete signal.

[0027] In a preferred embodiment, the step of performing interference detection in a slow time dimension on a range unit having asynchronous interference in a fast time dimension includes:

[0028] Calculate the median amplitude M of all slow time dimension distance units under distance unit j j ;

[0029] Calculate the amplitude of each slow time dimension distance unit under distance unit j. The amplitude of the i-th slow time dimension distance unit under distance unit j is expressed as P ij ;

[0030] Calculate the amplitude P of the distance unit in the slow time dimension ij and median M jThe ratio R ij ;

[0031] Set the length of the two-dimensional window L and calculate L ratios R within the two-dimensional window ij The mean R mean ;

[0032] If the mean R mean If the distance unit j is greater than the threshold C1, the distance unit j is marked as an interference unit, otherwise it is not marked.

[0033] In a preferred embodiment, the median magnitude M is calculated j If the radar rotates mechanically in azimuth, the N data in the slow time dimension are segmented and the median value M of each segment is calculated. jn , calculate the median M jn and median amplitude M j The ratio of the median M jn and median amplitude M j When the ratio is greater than the threshold M1, the median amplitude M j Replaced by the median M jn .

[0034] In a preferred embodiment, the threshold value C1 when the range unit is in a static clutter area is reduced by 1-3 dB compared to the threshold value C1 when the range unit is in a clean area.

[0035] In a preferred embodiment, the step of performing asynchronous interference suppression on the marked interference unit includes:

[0036] Perform linear interpolation using the data before and after the interference unit, and replace the interference unit with the interpolated data;

[0037] When the interference unit is the first or last distance unit in the slow time dimension, it is replaced by an adjacent distance unit respectively.

[0038] In a second aspect, the present invention provides a device for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features, which is used to execute the above-mentioned method for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features;

[0039] The apparatus for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features includes a DSP platform; an asynchronous interference suppression module is implemented in the DSP platform, and the asynchronous interference suppression module includes:

[0040] A data sampling unit, used to obtain CPI data and clutter map data;

[0041] An interference identification unit is used to determine whether there is asynchronous interference in the fast time dimension where the range unit in the CPI data is located using the clutter map data;

[0042] An interference marking unit is used to perform interference detection in the slow time dimension on the distance unit with asynchronous interference in the fast time dimension and mark the interference unit;

[0043] The interference suppression unit is used to perform asynchronous interference suppression on the interference unit.

[0044] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0045] 1. The present invention can effectively solve the problem of asynchronous interference on radar. By analyzing the multi-dimensional characteristics of asynchronous interference, such as amplitude, spectrum and phase, the asynchronous interference identification method established can quickly locate the interference on the basis of the fast time dimension distance unit and accurately identify the interference, thereby improving the interference identification rate and correct recognition rate.

[0046] 2. The present invention uses clutter map data to divide clean areas into static clutter areas, establishes a clutter phase alignment factor in the static clutter area to quickly locate whether interference exists; and uses a spectral flatness factor in the clean area to quickly locate whether interference exists. This can avoid the step of detecting each I / Q data unit in traditional methods, compress the processing time of the asynchronous interference suppression module, effectively improve the recognition rate of asynchronous interference, and can further improve the interference recognition rate, enhancing the radar's detection capability in complex backgrounds.

[0047] 3. The present invention considers the amplitude characteristics of interference in both fast-time and slow-time dimensions, and uses the median value that is more representative of the amplitude characteristics to identify interference, effectively improving the interference identification effect under high duty cycle and low power conditions.

[0048] 4. This invention dynamically adjusts the interference recognition threshold for different regions, addressing the high incidence of false targets in complex electromagnetic environments. Adaptive adjustments are made to mechanically rotating radars, effectively reducing the impact of radar fluctuations caused by rotation on interference recognition. This increases the accuracy of interference recognition in complex environments and broadens its applicability to radars of different systems.

[0049] 5. The present invention reliably restores the original information after identifying the interference, minimizing the impact of the interference on the original data.

[0050] 6. In general, the present invention can significantly improve the detection capability and signal quality of the radar system, effectively reduce the impact of asynchronous interference on radar detection, optimize resource utilization, and enhance the overall performance and application value of the radar system. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1A system block diagram of a radar echo processing system to which a method and device for identifying and suppressing primary radar asynchronous interference based on multi-dimensional features is applied in an embodiment of the present invention.

[0052] Figure 2 An input-output relationship diagram of a primary radar asynchronous interference identification and suppression device based on multi-dimensional features provided by an embodiment of the present invention.

[0053] Figure 3 This is an overall flow chart of a method for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features provided by an embodiment of the present invention.

[0054] Figure 4 Schematic diagram of CPI data sampled in an embodiment of the present invention.

[0055] Figure 5 This is a flowchart of a marking interference unit in an embodiment of the present invention.

[0056] Figure 6a Schematic diagram of the effect before interference suppression in an embodiment of the present invention.

[0057] Figure 6b Schematic diagram of the interference suppression effect in an embodiment of the present invention. DETAILED DESCRIPTION

[0058] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0059] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0060] like Figure 1 As shown, the entire radar echo processing system includes echo reception, down-conversion, analog-to-digital conversion, signal processing, target detection, data processing, etc. The present invention provides a method and device for identifying and suppressing asynchronous interference in a primary radar based on multi-dimensional features. The method and device are applied to the signal processing link in the radar echo processing system, and effectively identify and suppress asynchronous interference by processing baseband I / Q data after pulse compression.

[0061] like Figure 2As shown in the figure, the signal processing link of the entire radar echo processing system is completed based on the FPGA (Field Programmable Gate Array) platform and the DSP (Digital Signal Processing) platform. The FPGA platform completes pulse compression, and the baseband I / Q data after pulse compression is transmitted as input to the DSP platform's storage space DDR3 (Double-Data-Rate Three Synchronous Dynamic Random Access Memory) for asynchronous interference suppression and subsequent signal processing.

[0062] like Figure 3 As shown, an embodiment of the present invention provides a method for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features, comprising the following steps:

[0063] S100, obtain data, including CPI data and clutter map data:

[0064] For CPI data: a continuous address space is opened in the DSP platform's memory space DDR3, dedicated to storing baseband I / Q data and its corresponding frame header information. After a pulse is transmitted once, N distance units are sampled. After M pulse samples, a complete CPI (Coherent Processing Interval) data is formed, such as Figure 4 As shown in Figure 2, pulse sampling is slow time dimension sampling, and distance sampling corresponding to the distance unit is fast time dimension sampling.

[0065] For clutter map data: A continuous address space is allocated within the DSP platform's DDR3 memory space to store clutter map data. This clutter map data is generated within the DSP platform after multiple radar scans and is used to distinguish between static clutter and clean areas within the radar's scan range. The clutter map data is represented as a 0-1 matrix, where 0 indicates a clean area for a range cell and 1 indicates a static clutter area for a range cell. When the baseband I / Q data transmission for a CPI data set is complete, the signal processing start flag is triggered, and signal processing begins.

[0066] S200: Using the clutter map data, determine whether there is asynchronous interference in the fast time dimension where the range unit in the CPI data is located:

[0067] After step S100, the clutter map data and the baseband I / Q data in the CPI data are obtained, and the baseband I / Q data in the CPI data are judged by the 01 matrix of the clutter map data:

[0068] (1) When the clutter map data corresponding to the range unit is 0, the spectrum flatness factor of the range unit is calculated. When the spectrum flatness factor is greater than the spectrum flatness threshold (set according to needs and actual conditions), it is determined that asynchronous interference exists in the fast time dimension where the range unit is located;

[0069] Among them, the spectral flatness factor is introduced to quickly locate whether there is interference in the fast time dimension data of the clean area. The calculation of the spectral flatness factor involves Fourier transform. Therefore, the calculation method of the spectral flatness factor includes:

[0070] The spectral components of the discrete signal of the baseband I / Q data are sorted from low value to high value, some of the lowest values ​​are removed from the sorted spectral components, and the inverse of the standard deviation of the remaining spectral components is calculated to obtain the spectral flatness factor; the spectral components are obtained by Fourier transforming the discrete signal of the baseband I / Q data. The calculation formula of the Fourier transform is the existing technology and will not be repeated here.

[0071] (2) When the clutter map data corresponding to the range unit is 1, the clutter phase alignment factor of the range unit is calculated. When the clutter phase alignment factor is greater than the clutter phase alignment threshold (set according to needs and actual conditions), it is determined that asynchronous interference exists in the fast time dimension where the range unit is located.

[0072] Among them, the clutter phase alignment factor is introduced to quickly detect whether there is asynchronous interference in the fast time dimension data in the static clutter area. The calculation method of the clutter phase alignment factor includes:

[0073]

[0074] in, represents the clutter phase alignment factor, Baseband I / Q data is n Discrete signal of discrete points, m is the number of discrete points of the discrete signal.

[0075] This step uses clutter map data to divide clean areas into static clutter areas. In the static clutter area, a clutter phase alignment factor is established to quickly locate whether interference exists. In the clean area, the spectrum flatness factor is used to quickly locate whether interference exists. This effectively improves the recognition rate of asynchronous interference, can greatly improve the recognition rate of interference, and enhance the radar's detection capability in complex backgrounds.

[0076] S300, performing interference detection in the slow time dimension on the distance unit with asynchronous interference in the fast time dimension, marking the interference unit, such as Figure 5 As shown:

[0077] S301, calculate the median amplitude M of all slow time dimension distance units under distance unit j j.

[0078] In some embodiments, if the radar is mechanically rotated in azimuth, the N data in the slow time dimension are segmented and the median value M of each segmented data is calculated respectively. jn , calculate the median M jn and median amplitude M j The ratio of the median M jn and median amplitude M j When the ratio is greater than the threshold M1, the median amplitude M j Replaced by the median M jn .

[0079] S302, calculate the amplitude of each slow time dimension distance unit under distance unit j, and the amplitude of the i-th slow time dimension distance unit under distance unit j is expressed as P ij .

[0080] S303, calculate the amplitude P of the slow time dimension distance unit ij and median M j The ratio R ij .

[0081] S304: Set the length L of the two-dimensional window and calculate L ratios R in the two-dimensional window. ij The mean R mean .

[0082] S305, if the mean R mean If the value of the distance cell j is greater than the threshold C1, the distance cell j is marked as an interference cell; otherwise, it is not marked. The threshold C1 when the distance cell is in a static clutter area is 1-3 dB lower than the threshold C1 when the distance cell is in a clean area. Dynamic adjustment of the interference recognition threshold in different areas is performed, and adaptive adjustment is performed for radars that mechanically rotate in azimuth. This effectively reduces the impact of the fluctuation characteristics of the radar's rotation on the interference recognition effect, and increases the correct recognition rate of interference in complex backgrounds.

[0083] This step uses the amplitude characteristics to accurately locate the slow time dimension unit where the interference is located, and uses the median value that better represents the amplitude characteristics to identify the interference, effectively improving the identification effect of interference under high duty cycle and low power conditions. The amplitude calculation method is as follows:

[0084]

[0085] in, Indicates the amplitude, Indicates baseband I / Q data in n Discrete signal with discrete points.

[0086] Step S400: Perform asynchronous interference suppression on the marked interference unit:

[0087] Use the data before and after the interference unit to perform linear interpolation and replace the interference unit with the interpolated data; let the coordinates of the data before and after the interference unit be ( )and( ), the linear interpolation formula is as follows:

[0088]

[0089] in,( ) is the data coordinate of the interference unit.

[0090] In particular, when the distance unit is the first or last in the slow time dimension, it is replaced by the adjacent distance unit. Figure 6a 、 Figure 6b As shown, it can be seen that this step reliably restores the original information after identifying the interference, minimizing the impact of the interference on the original data.

[0091] Based on the same technical concept, an embodiment of the present invention further provides a device for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features, so as to execute the aforementioned method for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features;

[0092] like Figure 1 、 2 As shown, the apparatus for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features includes a DSP platform; an asynchronous interference suppression module is implemented in the DSP platform, and the asynchronous interference suppression module includes:

[0093] A data sampling unit, used to obtain CPI data and clutter map data;

[0094] An interference identification unit is used to determine whether there is asynchronous interference in the fast time dimension where the range unit in the CPI data is located using the clutter map data;

[0095] An interference marking unit is used to perform interference detection in the slow time dimension on the distance unit with asynchronous interference in the fast time dimension and mark the interference unit;

[0096] The interference suppression unit is used to perform asynchronous interference suppression on the interference unit.

[0097] The working principles of the functional modules and units in the above-mentioned device can be referred to the description in the above-mentioned method embodiment, which will not be repeated here.

[0098] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features, characterized in that: include: Acquire data, including CPI data and clutter map data; Using the clutter map data, determining whether there is asynchronous interference in the fast time dimension where the range unit in the CPI data is located; For distance units with asynchronous interference in the fast time dimension, interference detection in the slow time dimension is performed and the interference units are marked; Performing asynchronous interference suppression on the marked interference units; The data obtained: The CPI data is obtained by performing M pulse sampling of N distance units on the baseband I / Q data; wherein the pulse sampling is a slow time dimension sampling, and the distance sampling corresponding to the distance unit is a fast time dimension sampling; The clutter map data is expressed as a 01 matrix, where 0 indicates that the distance unit is a clean area, and 1 indicates that the distance unit is a static clutter area; The determining whether there is asynchronous interference in the fast time dimension where the range unit in the CPI data is located by using the clutter map data includes: The baseband I / Q data in the CPI data is judged by the 01 matrix of the clutter map data: When the clutter map data corresponding to the distance unit is 0, the spectral flatness factor of the distance unit is calculated. When the spectral flatness factor is greater than the spectral flatness threshold, it is determined that asynchronous interference exists in the fast time dimension where the distance unit is located; When the clutter map data corresponding to the range unit is 1, the clutter phase alignment factor of the range unit is calculated. When the clutter phase alignment factor is greater than the clutter phase alignment threshold, it is determined that asynchronous interference exists in the fast time dimension where the range unit is located.

2. The method for identifying and suppressing primary radar asynchronous interference based on multi-dimensional features according to claim 1, characterized in that: The calculation method of the spectral flatness factor includes: The spectral components of the discrete signal of the baseband I / Q data are sorted from low value to high value, some of the lowest values ​​are removed from the sorted spectral components, and the inverse of the standard deviation of the remaining spectral components is calculated to obtain the spectral flatness factor; the spectral components are obtained by Fourier transforming the discrete signal of the baseband I / Q data.

3. The method for identifying and suppressing primary radar asynchronous interference based on multi-dimensional features according to claim 1, characterized in that: The calculation method of the clutter phase alignment factor includes: in, represents the clutter phase alignment factor, Baseband I / Q data is n Discrete signal of discrete points, m is the number of discrete points of the discrete signal.

4. The method for identifying and suppressing primary radar asynchronous interference based on multi-dimensional features according to claim 1, characterized in that: The performing interference detection in the slow time dimension on the distance unit having asynchronous interference in the fast time dimension includes: Calculate the median amplitude M of all slow time dimension distance units under distance unit j j ; Calculate the amplitude of each slow time dimension distance unit under distance unit j. The amplitude of the i-th slow time dimension distance unit under distance unit j is expressed as P ij ; Calculate the amplitude P of the distance unit in the slow time dimension ij and median M j The ratio R ij ; Set the length of the two-dimensional window L and calculate L ratios R within the two-dimensional window ij The mean R mean ; If the mean R mean If the distance unit j is greater than the threshold C1, the distance unit j is marked as an interference unit, otherwise it is not marked.

5. The method for identifying and suppressing primary radar asynchronous interference based on multi-dimensional features according to claim 4, characterized in that: Calculate the median amplitude M j If the radar rotates mechanically in azimuth, the N data in the slow time dimension are segmented and the median value M of each segment is calculated. jn , calculate the median M jn and median amplitude M j The ratio of the median M jn and median amplitude M j When the ratio is greater than the threshold M1, the median amplitude M j Replaced by the median M jn .

6. The method for identifying and suppressing primary radar asynchronous interference based on multi-dimensional features according to claim 4, characterized in that: The threshold C1 when the range cell is in a static clutter area is reduced by 1-3 dB compared to the threshold C1 when the range cell is in a clean area.

7. The method for identifying and suppressing primary radar asynchronous interference based on multi-dimensional features according to claim 1, characterized in that: The step of performing asynchronous interference suppression on the marked interference unit includes: Perform linear interpolation using the data before and after the interference unit, and replace the interference unit with the interpolated data; When the interference unit is the first or last distance unit in the slow time dimension, it is replaced by an adjacent distance unit respectively.

8. A device for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features, characterized in that: Used to execute the method for identifying and suppressing primary radar asynchronous interference based on multi-dimensional features as described in any one of claims 1 to 7; The apparatus for identifying and suppressing asynchronous interference of a primary radar based on multi-dimensional features includes a DSP platform; an asynchronous interference suppression module is implemented in the DSP platform, and the asynchronous interference suppression module includes: A data sampling unit, used to obtain CPI data and clutter map data; An interference identification unit is used to determine whether there is asynchronous interference in the fast time dimension where the range unit in the CPI data is located using the clutter map data; An interference marking unit is used to perform interference detection in the slow time dimension on the distance unit with asynchronous interference in the fast time dimension and mark the interference unit; The interference suppression unit is used to perform asynchronous interference suppression on the interference unit.

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