Airborne early warning radar moving target detecting method based on clutter ridge guiding vector

Abstract

The invention discloses an airborne early warning radar moving target detecting method based on a clutter ridge guiding vector and relates to the radar technique. The method comprises the steps of (1) receiving the space-time two-dimensional echo data of an airborne early warning radar device by means of an airborne early warning radar antenna, (2) determining a normalization space-time two-dimensional frequency point corresponding to a clutter ridge curve position relevant to the space-time two-dimensional echo data, (3) constructing a clutter ridge guiding vector basis matrix according to the normalization space-time two-dimensional frequency point corresponding to the clutter ridge curve position, (4) acquiring data left after fitting, and (5) conducting cell averaging constant false alarm rate detection on the data left. The method mainly solves the problem that in practical application of traditional space-time adaptive processing, the amount of calculation is huge, and the requirement for the number of independent identically distributed samples is high. The method has good application prospects in the improvement of the airborne early warning radar moving target detecting performance.

Description

technical field [0001] The invention belongs to the technical field of communication, relates to radar technology, in particular to an airborne early warning radar moving target detection method based on a clutter ridge steering vector, which is used for airborne early warning radar signal processing. Background technique [0002] The main task of airborne early warning radar is to detect targets in complex clutter background and to locate and track them. Effective suppression of clutter is the core means to improve the performance of early warning radar. Space-time adaptive processing (STAP) technology makes full use of airspace and time domain information, while coherently accumulating target signals, and filters ground clutter through space-time adaptive processing to realize airborne radar detection. efficient detection of targets. For example, the E2-D airborne early warning radar of the United States adopts this technology. In practical applications, STAP technology ...

AI Technical Summary

Problems solved by technology

In practical applications, STAP technology mainly has the following two problems: First, in a non-uniform clutter environment, it is necessary to obtain enough independent and identically distributed (IID) training samples for estimating the covariance matrix It is very difficult; secondly, even if the requirements of the training samples are met, the problem of excessive calculation in all-time processing will make it difficult to guarantee real-time performance

However, the main disadvantage of this method is that the number of overcomplete bases for sparsely representing the clutter spectrum is undetermined, but it is much larger than the system degrees of freedom. In practice, the system degrees of freedom are usually tens of thousands, so that in each distance unit sample The amount of calculation required in the process of reconstruction of the covariance matrix is ​​very large, which is not conducive to real-time processing, thus affecting its actual engineering application effect

However, this method still has the disadvantage that the notch width of the filter designed to suppress the clutter is artificially set, and cannot adaptively perceive the clutter ridges in the actual data. The minimum detectable speed becomes larger, which is very unfavorable for the detection of low-speed small targets

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