In this paper, a fast and computationally efficient joint presence detection and localization method is proposed for the non-cooperative direct sequence spread spectrum (DS-SS) signals. The method uses spatially distributed wideband sensor array output in a sparse way. It is applicable to long and timely varying spreading coded DS-SS signals. The proposed method uses the linearity of phase response between the cross elements of the spatial covariance matrices (R) along the signal bandwidth. This linearity in frequency domain is also used to estimate the time difference of arrival (TDOA) between sensors for the localization of these signals. A new sparse spatial covariance matrix (R) estimation technique which is called as block of consecutive frequency bins (BCFB) is also proposed. Hence, the computational complexity and data sharing rate between sensors are quite reduced according to the conventional incoherent signal subspace processing (ISSP) method. It is shown in simulations that the proposed BCFB method improves the TDOA estimation performance in low signal to noise ratio (SNR) and it attains to the Cramer Rao Lower Bound (CRLB) with greatly reduced processing time.
['Can Uysal', 'Tansu Filik']
A joint detection and localization method for non-cooperative DS-SS signals