A Dimensionality Reduction Method for Clutter Suppression Based on Eigenbeam Adaptive Beam Domain FSA

An adaptive beam and clutter suppression technology, applied in radio wave measurement systems, instruments, etc., can solve problems such as large amount of computation, high requirements for training samples, and increased system dimension, so as to reduce the dimension of the processor and reduce the number of training samples. The effect of reducing the number and reducing the dimension of the system

Active Publication Date: 2021-11-19
XIDIAN UNIV
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  • Summary
  • Abstract
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Problems solved by technology

[0004] However, because the full-dimensional space-time adaptive processing method utilizes all spatial equivalent array elements and time-domain pulse sampling, the system dimension is large, the computational complexity is high, and it requires high training samples, which is difficult to achieve in actual processing.
When processing the actual measurement data in engineering, the processing method of time-domain sliding window first and then time-space joint processing, with the increase of the number of spatial channels, the system dimension increases, and the processing still has a large amount of calculation. The sample still has high requirements and cannot meet the actual application requirements

Method used

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  • A Dimensionality Reduction Method for Clutter Suppression Based on Eigenbeam Adaptive Beam Domain FSA
  • A Dimensionality Reduction Method for Clutter Suppression Based on Eigenbeam Adaptive Beam Domain FSA
  • A Dimensionality Reduction Method for Clutter Suppression Based on Eigenbeam Adaptive Beam Domain FSA

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Embodiment 1

[0056] See figure 1 , figure 1 It is a schematic flowchart of a clutter suppression and dimensionality reduction method based on eigenbeam adaptive beam domain FSA provided by an embodiment of the present invention, including:

[0057] Step 1: Get the FSA data vector;

[0058] First, perform A / D sampling on N space equivalent array elements of the radar to obtain K+2 pulse echo data in one CPI; wherein, the K+2 pulse echo data include echoes of L samples information;

[0059] Then in each space equivalent array element, the K+2 pulse data is processed three times in the time domain sliding window, and three sets of data consisting of the 1st~K, 2~K+1 and 3~K+2 pulses are respectively obtained;

[0060] Finally, carry out K-point DFT on the three sets of data and transfer them to the Doppler domain to obtain the FSA data vector; wherein, for the same Doppler channel, the three sets of data respectively transform L of the N spatially equivalent array elements into the Doppler...

Embodiment 2

[0104] The effects of the present invention will be further described below in conjunction with simulation experiments.

[0105] 1. Simulation conditions

[0106] The airborne multi-channel radar in the experimental simulation of the present invention adopts the one-shot-multiple-receive mode, works in the front side view, the angle between the beam center and the array antenna plane is 90 degrees, and there are 10 equivalent array elements to receive, and the array element spacing is 0.123 meters, the number of pulses accumulated in one CPI is 200, the pulse repetition frequency is 3000 Hz, the working wavelength is 0.246 meters, the shortest detection distance of the radar is 7 kilometers, the distance resolution is 20 meters, the number of samples is 600, the platform flight The altitude is 6 kilometers, the speed is 100 meters per second, the target is located in the center of the beam, and the radial speed is 53 meters per second.

[0107] 2. Simulation content and resul...

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Abstract

The invention discloses a clutter suppression and dimensionality reduction method for adaptive beam domain FSA based on eigenbeams, comprising: acquiring FSA data vectors; acquiring feature spaces; and performing beam domain adaptation on the FSA data vectors according to the feature spaces The dimensionality reduction processing obtains a dimensionality-reduced data vector; performing clutter suppression and adaptive filtering processing on the dimensionality-reduction data vector to obtain range-Doppler domain data after clutter suppression. The clutter suppression and dimensionality reduction method provided by the present invention has a certain degree of self-adaptability. While realizing clutter suppression, it reduces the adaptive processing dimension, reduces the standard for selecting samples, and reduces the uniform clutter samples required for processing. The number and the amount of calculation have improved the practicability of the algorithm.

Description

technical field [0001] The invention belongs to the technical field of moving platform radar, and in particular relates to a clutter suppression and dimensionality reduction method based on an adaptive beam domain FSA of characteristic beams. Background technique [0002] Radar is an electronic device that uses electromagnetic waves to detect objects. Usually, in order to effectively improve the air surveillance capability, radar systems are installed on aircraft or artificial satellites. Due to the high-speed movement characteristics of the airborne / spaceborne radar platform, when the radar works in the down-looking state, the main lobe clutter Doppler spectrum of the scene is severely broadened, resulting in weak and slow targets being submerged in the clutter and unable to be directly detected. Therefore, the premise of using airborne / spaceborne radar to realize the task of moving target detection is to suppress the strong clutter in the scene, so that the submerged weak...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S7/36G01S7/41
CPCG01S7/36G01S7/41
Inventor 杨志伟李婧雅田敏雷赫黄帅
Owner XIDIAN UNIV
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