Improvement and analysis of multi-station TDOA positioning algorithm based on MSVD

Aiming at the failure of multi-station TDOA positioning caused by factors such as unreasonable sensor distribution and measurement noise, a new robust multi-station TDOA positioning method based on Modified Singular Value Decomposition (MSVD) is proposed. In the new algorithm, we use the condition number to evaluate the ill-conditioned degree of the observation equation, and then use the idea of truncated singular value decomposition to correct the singular value with higher ill-conditioned, so as to suppress the influence of measurement noise. The new algorithm effectively considers the resolution and variance of positioning parameter evaluation, and achieves effective suppression of random observation noise in the observation equation. The simulation results show that, compared with the least squares method, the new algorithm can adapt to various multi-station deployment situations, and the positioning results are more accurate and stable.