Distributed target detection method based on antisymmetric transformation and parameter adjustability

Abstract

The invention provides a distributed target detection method based on antisymmetric transformation and parameter adjustability, and belongs to the technical field of communication. The distributed target detection method comprises the following implementation steps: (1) obtaining echo signals and training samples of distributed targets; (2) performing antisymmetric transformation on the echo signals and the training samples of the distributed targets; (3) performing parameterization processing on a steering vector mismatch sensitive detector and a steering vector mismatch robust detector to construct a parameter-adjustable detector; (4) determining a detection threshold of the detector via a Monte Carlo experiment; (5) calculating a detection statistical magnitude of the parameter-adjustable detector; and (6) comparing the detection statistical magnitude with the detection threshold to determine the presence or absence of the target. By adoption of the distributed target detection method provided by the invention, under the condition of steering vector mismatch, the rejection performance and the recognition ability of mismatch signals are improved, the application range of the target detection method is expanded, and the distributed target detection method can be applied to the distributed target detection under the conditions of high-resolution radar steering vector mismatch and training sample deficiency.

Description

technical field [0001] The invention belongs to the field of communication technology, and relates to a distributed target detection method, in particular to a distributed target detection method based on antisymmetric transformation and adjustable parameters, which can be used under conditions of high-resolution radar guidance vector mismatch and insufficient training samples distributed object detection. Background technique [0002] Signal detection refers to the process of extracting useful signals from received signals containing interference noise. The influencing factors that determine the performance of signal detection are roughly divided into detection accuracy, adaptability to the environment, rejection performance and recognition ability. The working modes of the radar are roughly divided into radar scanning mode, radar tracking mode and other modes. Target detection in clutter environment is one of the most basic tasks of radar, and the target detection method...

AI Technical Summary

Problems solved by technology

The shortcomings of this method are: the detector designed by this method is a robust detector for steering vector mismatch, which cannot be applied to radar tracking mode, and is not suitable for various application environments under the condition of steering vector mismatch. Poor rejection and identification of mismatched signals

[0007] In adaptive detection, all adaptive detectors assume a reference steering vector, but the influence of many error factors in practical applications, such as mutual coupling between array elements, amplitude and phase errors, and array element position errors, will cause actual steering There is a mismatch between the vector and the reference steering vector

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