Line spectrum tracking method in transformed signal space for underwater moving targets in low signal-to-noise ratio environment.

Abstract

Line spectrum tracking is an essential signal-processing method for underwater passive detection. However, its performance is often seriously degraded due to signal fluctuation, especially in low signal-to-noise ratio scenarios. In this paper, based on signal space transformation and hidden Markov model, a signal trajectory tracking method is proposed for underwater moving target detection and parameter estimation. With this method, tracking the varying line spectrum trajectory in three-dimensional frequency-azimuth-time signal space is constrained onto a two-dimensional plane in the transformed signal space. Not only is the computation complexity reduced, but the ability to track weak line spectrums and estimate target parameters is improved. The performance of this method is verified with numerical simulations and experimental data processing.