Method for estimating incoming wave directions of targets in radar based on external illuminators by aid of GPU (graphics processing unit)

Abstract

The invention discloses a method for estimating incoming wave directions of targets in radar based on external illuminators by the aid of a GPU (graphics processing unit). The method mainly solves problems that the traditional method for estimating incoming wave directions of targets is constrained by signal processing platforms and algorithms and the requirement on instantaneity cannot be met. The technical scheme includes that the method comprises performing time-domain interference cancellation and range-Doppler two-dimensional correlation processing on unit data and then loading the unit data into a GPU-based computing system on the basis of an idea of compressed sensing; creating a sensing matrix; sparsely reconstructing and solving azimuth on the basis of compressed sensing in the GPU by a parallel process according to the processed unit data and the sensing matrix; acquiring solved azimuth signal vectors; reconstructing the incoming wave directions of the targets by the aid of the azimuth signal vectors. The method has the advantages of simplicity in building hardware platforms, good stability, high computation speed and expandability and easiness in development, and is applicable to estimating incoming wave directions of multiple targets in radar based on external illuminators.

Description

technical field [0001] The invention belongs to the technical field of radar, and relates to a radar signal processing method, in particular to a method for estimating the incoming wave direction of a target in an external radiation source radar by using a GPU, and is used for precise direction finding of the target. technical background [0002] In recent years, more and more attention has been paid to the passive radar detection technology using radio, television, satellite and other civilian sources of radiation. The passive radar system itself does not need to transmit signals, but uses the electromagnetic wave signals already in the environment or emitted by the target itself for target detection and positioning. Comprehensive "four resistance" potential. [0003] According to the different detection objects, passive radar is mainly divided into two categories: one is to use the radiation of the detection target itself for detection and direction finding; the other is ...

AI Technical Summary

Problems solved by technology

These two algorithms usually require multiple snapshots to accumulate, and the processing time is too long to meet real-time requirements. At the same time, the estimation effect of multiple sources and related sources is poor, and the requirements for signal-to-noise ratio are high and the anti-noise performance is poor.

Since the direct wave and multipath energy in the signal acquired by the external radiation source radar are very strong, in order to suppress the interference and improve the signal-to-noise ratio of the target echo, it is necessary to perform time-domain interference cancellation and range-Doppler two on the target wave. However, after time-domain interference cancellation and range-Doppler two-dimensional correlation processing, the data that can be applied to direction finding is only a single snapshot. At this time, traditional subspace algorithms such as multiple signal classification MUSIC will fail

At the same time, in the process of realizing the direction finding of the target, the data processing is mainly carried out through the development of a special signal processing board, but the development cost of this hardware platform is relatively high, and with the increase of the calculation amount of data processing, generally only rely on doubling Increase the size of the hardware to implement the function

In addition, the development time and debugging cycle of the signal board are long, and the operability is poor. Moreover, as the hardware scale doubles, the development difficulty becomes greater and the cost increases, which cannot meet the real-time performance and cost saving of scientific research experiments and applications. Waiting for demand

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