Transmission Diversity Smoothing for Multi-Target Localization

Abstract

A new method for target localization by radar or sonar systems based on spatially coded signal transmission is proposed. Recently, it has been shown that spatially-coded signal transmission allows us to obtain virtual sensors. We show that for any array geometry, these virtual sensors are grouped into subarrays with identical structures. The transmission diversity, embedded in the spatially-coded signal model, is used to spatially smooth the signal covariance matrix in order to enable the use of eigenstructure-based methods for multiple coherent target localization. Unlike conventional spatial smoothing and forward-backward averaging, the proposed transmission diversity smoothing (TDS) algorithm is not limited to uniform or symmetric arrays, and does not decrease the array aperture. The performance of the algorithm implemented with MUSIC is tested using simulations and compared to the spatial smoothing method. The results show that the TDS algorithm is consistent and outperforms the spatial smoothing method.