A linear-correction method is developed for source position and velocity estimation using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements. The proposed technique first obtains an initial source location estimate using the first-step processing of an existing algebraic algorithm. It then refines the initial localization result by estimating via weighted least-squares (WLS) optimization and subtracting out its estimation error. The new solution is shown to be able to achieve the Cramer-Rao lower bound (CRLB) accuracy and it has better accuracy over several benchmark methods at relatively high noise levels.

Long-term coherent integration can significantly improve the ability to detect maneuvering targets by radar. Especially for weak targets, longer integration times are needed to improve. But for non-radially moving targets, the time-varying angle between target moving direction and radar line of sight will cause non-linear range migration (NLRM) and non-linear Doppler frequency migration (NLDFM) within long-time coherent processing, which precludes existing methods that ignore angle changes, and seriously degrades the performance of coherent integration. To solve this problem, an efficient method based on Radon Fourier transform (RFT) with modified variant angle model (ARFT) is proposed. In this method, a new parameter angle is introduced to optimize the target motion model, and the NLRM and NLDFM are eliminated by range-velocity-angle joint three-dimensional searching of ARFT. Compared with conventional algorithms, the proposed method can more accurately compensate for the NLRM and NLDFM, thus achieving better integration performance and detection probability for non-radial moving weak targets. Numerical simulations verify the effectiveness and advantages of the proposed method.