Tracking of the multi-dimensional parameters of a target signal using particle filtering

In this contribution, a low-complexity particle filter (PF) is proposed to track the parameters of the signal reflected by a target illuminated with a digital-video-broadcast terrestrial (DVB-T) signal. The tracked parameters are the delay (time of arrival), the azimuth and elevation of arrival, the Doppler frequency, the complex amplitude of the target signal, as well as the rates of change of all but the last parameter. The proposed PF tracks these parameters based on samples of the target signal by assuming that the temporal behaviour of these parameters is governed by a multi-dimensional linear state-space model. The algorithm has an additional resampling step specifically designed to cope with the highly concentrated multi-dimensional posterior probability density function of the parameters. This step allows for tracking the parameters of the target signal with only a few particles, e.g. 50, leading to low computational complexity. Simulation results show that the PF outperforms the maximum-likelihood estimator applied to individual samples of the target signal in terms of higher accuracy and robustness. Under certain conditions usually met in reality the proposed PF can be used to track the parameters of the signals contributed by individual targets in multi-target scenarios.