A clutter map detection method and system

Abstract

The present application relates to a kind of clutter map detection method and system, belong to radar signal processing technical field.The amplitude information of 8 detected units around the distance, velocity plane of the detected unit and the amplitude information of 4 detected units with the same distance, velocity, adjacent azimuth, pitch of the detected unit are selected to obtain the detection threshold reference value by big processing.The present application uses the method of clutter map detection neighborhood selection, effectively suppresses slow target, so as to eliminate the false alarm caused by the movement of low-speed target in distance, doppler, azimuth, pitch and other directions.

Description

Technical Field

[0001] The present invention belongs to the field of radar signal processing technology and relates to a clutter pattern detection method and system. This method can be used to design detection thresholds in clutter pattern detection processing. It is primarily applicable to target detection processing in high-resolution range radars in the presence of slow-moving targets. This method can effectively reduce false alarms caused by slow-moving targets. Background Art

[0002] Due to limited operating environments, low-altitude aircraft detection radars are often significantly affected by false alarms caused by small, slow-moving targets. Due to the high range and Doppler resolution of low-altitude surveillance radars, traditional clutter map processing can fail due to slow update speeds. Traditional clutter map detection technology uses update coefficients to adjust clutter map detection performance. Faster clutter map update frequencies increase detection losses, while too slow a clutter map update frequency is ineffective. This is particularly true when tiny scatterers are present in the air, as they slowly move through the air, generating a large number of primary traces. In this situation, using a range-dependent constant false alarm detection algorithm requires increasing the detection threshold to suppress these traces. Increasing the detection threshold also means a loss in detection range, degrading radar performance. The present invention improves the signal processing system's suppression of small, slow-moving targets by improving the clutter map detection algorithm. Summary of the Invention

[0003] Technical problems to be solved

[0004] In order to overcome the shortcomings of the prior art, the present invention provides a clutter pattern detection method and system to improve the suppression effect of the clutter pattern on slow and small targets.

[0005] Technical Solution

[0006] A clutter pattern detection method is characterized by the following steps:

[0007] Step 1: Divide the detection space into detection units according to the target detection space, and establish a 4-dimensional clutter map detection space of azimuth, pitch, distance, and speed. Each detection unit in the detection space stores the echo signal amplitude information; the detected targets are randomly distributed in the 4-dimensional space of azimuth, pitch, distance, and speed; in the initialization state, the target amplitude information data stored in the clutter map is set to zero;

[0008] Step 2: When echo information is input, the stored clutter information is updated; the input echo information includes the current beam azimuth, pitch position, distance, and velocity 2D plane amplitude information; when the clutter map is updated, a first-order recursive filtering process is performed on each detection unit on the distance and velocity 2D plane:

[0009]

[0010] in y(n)Indicates the amplitude information stored by the detection unit in the clutter map at time n, x(n) Indicates the received echo amplitude information of the detection unit in the corresponding clutter image received at time n, K represents the clutter map update coefficient;

[0011] Step 3: Calculate the threshold reference value of the detected clutter map based on the clutter amplitude information of the neighborhood of the detected unit in the clutter map. The neighborhood clutter map units of the detected unit include: 8 detected units surrounding the detected unit in the distance and velocity plane, and 4 detection units with the same distance and velocity as the detected unit, and adjacent in azimuth and elevation. For each detected unit, the amplitude information of 13 clutter map units is required to calculate the detection threshold reference value. The detection threshold reference value is obtained by selecting the largest amplitude information of these 13 clutter map units.

[0012] Step 4: Multiply the detection threshold reference value by the detection threshold adjustment coefficient to obtain the detection threshold value. Compare the amplitude of the detected unit in the current sampling period with the detection threshold value of the previous sampling period to determine whether a target exists. If the amplitude of the detected unit is greater than the detection threshold, the target is considered to exist; otherwise, the target does not exist.

[0013] A further technical solution of the present invention is: in step 3, when the target speed information changes relatively quickly, two or four adjacent clutter map units with the same distance unit as the detected unit are appropriately added.

[0014] A further technical solution of the present invention: in step 4, the detection threshold adjustment coefficient is designed to be 4.

[0015] A clutter map detection system includes a clutter map storage module, a clutter map update module, a clutter map threshold module, and a clutter map detection module. The clutter map storage module is used to store clutter information in a detection space; the clutter map update module updates the stored clutter information according to input echo information; the clutter map threshold module generates a detection threshold according to the stored clutter information; and the clutter map detection module outputs a target detection result according to the detection threshold and the input echo information.

[0016] A computer system, characterized in that it includes: one or more processors, and a computer-readable storage medium for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned method.

[0017] A computer-readable storage medium is characterized by storing computer-executable instructions, which are used to implement the above method when executed.

[0018] Beneficial effects

[0019] The present invention provides a clutter pattern detection method and system that effectively suppresses slow-moving targets by selecting the largest clutter pattern detection neighborhood. This technology can be expanded upon. If a signal detection system establishes a multidimensional clutter pattern based on range, Doppler, azimuth, and elevation, the largest clutter pattern can be selected within the detection unit neighborhood as the detection threshold, thereby eliminating false alarms caused by slow-moving targets moving in range, Doppler, azimuth, and elevation.

[0020] Compared with existing technologies, this method has the following features: 1. It effectively reduces false alarms caused by low-speed movement of clutter units. 2. It has good compatibility with traditional algorithms. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings are only for the purpose of illustrating particular embodiments and are not to be considered limiting of the present invention. Like reference symbols denote like parts throughout the drawings.

[0022] Figure 1 Clutter map detection process;

[0023] Figure 2 The detected unit is located in the middle area of ​​the clutter map plane;

[0024] Figure 3 The detected unit is located in the edge area of ​​the clutter map plane. DETAILED DESCRIPTION

[0025] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only intended to illustrate the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0026] The clutter map detection process is as follows: Figure 1 As shown in Figure 1, the radar echo signal input to the clutter map detection module is divided into two branches: one for generating the clutter map threshold, and the other directly enters the clutter map detection module to output the detection results. The clutter map threshold generation includes three processing modules: clutter map storage, clutter map update, and clutter map threshold.

[0027] The clutter map storage module is used to store clutter information in the detection space.

[0028] The clutter map updating module updates the stored clutter information according to the input echo information.

[0029] The clutter map threshold module generates a detection threshold according to stored clutter information.

[0030] The clutter map detection module outputs a target detection result according to a detection threshold and input echo information.

[0031] The clutter pattern detection method of the present invention mainly comprises the following steps:

[0032] 1. Clutter map storage

[0033] 2. Clutter map update

[0034] 3. Clutter map threshold

[0035] 4. Clutter map detection

[0036] Each step is as follows:

[0037] Step 1. Divide the target detection space into detection units. A four-dimensional clutter map detection space is established for azimuth, elevation, range, and velocity. Each detection unit in the detection space stores echo signal amplitude information. Detected targets are randomly distributed across the four-dimensional space of azimuth, elevation, range, and velocity. Initially, the target amplitude information stored in the clutter map is reset to zero.

[0038] Step 2. When echo information is input, the stored clutter information is updated. The input echo information includes the current beam position, range, and velocity amplitude information in the two-dimensional plane. When the clutter map is updated, a first-order recursive filter is performed on each detection unit in the two-dimensional plane of range and velocity.

[0039]

[0040] in y(n) Indicates the amplitude information stored by the detection unit in the clutter map at time n, x(n) Indicates the received echo amplitude information of the detection unit in the corresponding clutter image received at time n, K Represents the clutter map update coefficient. K The smaller it is, the slower the clutter map information is updated, which is more likely to cause false alarms; K The larger the value is, the faster the clutter map information is updated, which may cause missed alarms. In theory, K The value range of is [0,1]. In practical experience, K The selection is based on the actual background clutter movement. When the background clutter changes rapidly, K Take 1 / 8, when the background clutter changes slowly, K Take 1 / 32. Under the condition of periodic update of clutter map, according to the change of background clutter K Take a fixed value. When the beam scans the same space and the periodicity of the wave position changes greatly, K It can be adjusted appropriately. When the current beam scanning interval is greater than the average beam scanning interval, it can be increased. K When the current beam scanning interval is less than the average beam scanning interval, the value can be reduced. K By adjustingK value to accelerate the clutter graph to reach a stable state.

[0041] Step 3. Calculate the threshold reference value of the detected clutter map based on the neighborhood spatial clutter amplitude information of the detected unit in the clutter map. The neighborhood clutter map units of the detected unit include: 8 detected units around the distance and velocity plane where the detected unit is located, and 4 detection units that are at the same distance and velocity as the detected unit, and adjacent in azimuth and pitch. For each detected unit, the amplitude information of 13 clutter map units is required to calculate the detection threshold reference value. The detection threshold reference value is obtained by selecting the amplitude information of these 13 clutter map units. Since the target speed information changes relatively quickly, 2 or 4 neighboring clutter map units with the same distance unit as the detected unit can be appropriately added according to the changes in the clutter background. When the detected unit is located in the non-edge area of ​​the distance and velocity plane, the reference unit neighborhood is selected as follows: Figure 2 As shown in the figure, when the detected unit is located at the edge of the distance and velocity planes, the reference unit neighborhood is selected as follows: Figure 3 shown.

[0042] Step 4. Multiply the detection threshold reference value by the detection threshold adjustment coefficient to obtain the detection threshold value. The detection threshold adjustment coefficient can be adjusted according to the actual environment and is generally set to 4. The amplitude of the detected unit in the current sampling period is compared with the detection threshold value in the previous sampling period to determine whether a target is present. If the amplitude of the detected unit is greater than the detection threshold, the target is considered present; otherwise, the target is not present.

[0043] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present invention, and these modifications or replacements should all be included in the scope of protection of the present invention.

Claims

1. A clutter map detection method, characterized in that Here are the steps: Step 1: Divide the detection space into detection units according to the target detection space, and establish a 4-dimensional clutter map detection space of azimuth, pitch, distance, and speed. Each detection unit in the detection space stores the echo signal amplitude information; the detected targets are randomly distributed in the 4-dimensional space of azimuth, pitch, distance, and speed; in the initialization state, the target amplitude information data stored in the clutter map is set to zero; Step 2: When echo information is input, update the stored clutter information; The input echo information includes the current beam azimuth, pitch position, and velocity two-dimensional plane amplitude information. When the clutter map is updated, a first-order recursive filtering process is performed on each detection unit on the distance and velocity two-dimensional plane: in y(n) Indicates the amplitude information stored by the detection unit in the clutter map at time n, x(n) Indicates the received echo amplitude information of the detection unit in the corresponding clutter image received at time n, K represents the clutter map update coefficient; Step 3: Calculate the threshold reference value of the detected clutter map based on the clutter amplitude information of the neighborhood of the detected unit in the clutter map. The neighborhood clutter map units of the detected unit include: 8 detected units surrounding the detected unit in the distance and velocity plane, and 4 detection units with the same distance and velocity as the detected unit, and adjacent in azimuth and elevation. For each detected unit, the amplitude information of 13 clutter map units is required to calculate the detection threshold reference value. The detection threshold reference value is obtained by selecting the largest amplitude information of these 13 clutter map units. Step 4: Multiply the detection threshold reference value by the detection threshold adjustment coefficient to obtain the detection threshold value. Compare the amplitude of the detected unit in the current sampling period with the detection threshold value of the previous sampling period to determine whether a target exists. If the amplitude of the detected unit is greater than the detection threshold, the target is considered to exist; otherwise, the target does not exist.

2. A clutter pattern detection method according to claim 1, characterized in that: In step 3, when the target speed information changes relatively quickly, two or four adjacent clutter map units with the same distance unit as the detected unit are appropriately added.

3. The clutter pattern detection method according to claim 1, wherein: In step 4, the detection threshold adjustment coefficient is designed to be 4.

4. A clutter map detection system used in the method of claim 1, comprising a clutter map storage module, a clutter map update module, a clutter map threshold module, and a clutter map detection module, wherein the clutter map storage module is used to store clutter information in a detection space; the clutter map update module updates the stored clutter information based on input echo information; the clutter map threshold module generates a detection threshold based on the stored clutter information; and the clutter map detection module outputs a target detection result based on the detection threshold and the input echo information.

5. A computer system, characterized in that include: One or more processors, and a computer-readable storage medium for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the method of claim 1.

6. A computer-readable storage medium, characterized in that Computer-executable instructions are stored, and when the instructions are executed, they are used to implement the method of claim 1.

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