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A radar detection method based on knowledge-assisted permutation test

A replacement inspection and radar detection technology, applied in radio wave measurement systems, instruments, etc., can solve the problems of performance deterioration and limited application scope of the new knowledge-aided parameter CFAR algorithm, so as to improve performance, improve target detection speed, and reduce calculation. amount of effect

Inactive Publication Date: 2017-03-29
BEIHANG UNIV
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Problems solved by technology

[0004] The technical problem to be solved by the present invention is: Aiming at the performance deterioration of the traditional CFAR algorithm in the non-uniform clutter environment, and the problem that the application range of the new knowledge-assisted parameter CFAR algorithm is severely limited, a radar detection method based on knowledge-assisted permutation test is proposed. This method achieves excellent detection performance in complex clutter environments by cascading data selectors and non-parametric permutation tests, and has a wide range of applications

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Embodiment Construction

[0018] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0019] In the present invention, GIS information (GIS is Geographical Information System) is applied in radar target detection, has proposed the detection method of data selector cascade permutation inspection, has improved the detection performance in the complex clutter environment effectively; Simultaneously, designed A brand-new implementation method of permutation test, which greatly reduces the calculation amount of permutation test.

[0020] A kind of radar detection method based on knowledge-assisted permutation test of the present invention, its specific implementation process is as follows figure 2 As shown, it specifically includes the following three steps:

[0021] 1. According to the set false alarm probability and the basic parameters such as the reference unit and the number of pulses, calculate the sequence number of the th...

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Abstract

The invention discloses a radar detection method based on knowledge auxiliary permutation detection. The radar detection method comprises the following steps that (1) according to basic parameters of a set false alarm probability, a reference unit, a pulse number and the like, a sequence number of a threshold in all permutation statistical magnitudes in a descending order is calculated, further, all effective strategies are determined, and an effective strategy matrix is formed; (2) an effective reference unit is selected according to a to-be-detected unit and GIS information of a reference unit, and the effective reference unit and a sampling value of the to-be-detected unit form an effective data matrix; (3) a detection statistical magnitude is calculated according to data of the to-be-detected unit, a permutation calculation magnitude is calculated according to the effective strategy matrix, the threshold is determined accordingly, the detection statistical magnitude is compared with the threshold, and therefore a judgment is made. The radar detection method based on knowledge auxiliary permutation detection effectively improves the performance of an algorithm under a complex clutter environment, greatly widens the application range, effectively reduces the calculation magnitude, and increases the target detection speed.

Description

technical field [0001] The invention belongs to the field of radar target detection and relates to a radar detection method based on knowledge-assisted permutation inspection. Background technique [0002] Constant false alarm (CFAR) detection refers to a class of object detection techniques that can maintain a constant false alarm probability under the condition of changing clutter levels. Common CFAR detection algorithms can be divided into two categories: parametric CFAR and non-parametric CFAR. The parametric CFAR algorithm usually assumes that the distribution type of clutter is known, and only needs to estimate some unknown parameters, and based on this, the threshold is designed to make the target detection have constant false alarm characteristics under this assumption. The non-parametric CFAR algorithm does not need to know the distribution type of clutter, and it is a detection strategy with a constant false alarm probability under weak assumptions about backgroun...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S7/41
CPCG01S7/2928
Inventor 孙进平张旭旺付锦斌高飞
Owner BEIHANG UNIV
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