Abstract
In order to solve the problem that the traditional sonar detection method based on beam energy is not able to detect weak targets, a feature-based spatial beam target detection method is proposed in this paper. Firstly, the feature is extracted from the pre-formed beams in the whole spatial domain, and then using the relevance vector machine (RVM) for training, the probability output of target detection is obtained. Compared with traditional methods, this method can obtain excellent detection performance under the condition of low signal-to-noise ratio or signal-to-interference ratio. The probability output of this method can better represent the uncertainty of target detection, and it is also convenient for information fusion and other processing, which is different from the output of traditional binary detection. At the end of the paper, simulated data and experimental data both proved that this method is effective.
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