Research On TDOA And FDOA Localization Based On Cross Ambiguity Function Mapping Method

Passive source localization using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) from different receivers is a widely applied localization method. This paper first analyses the defects of conventional localization method. For example, conventional localization method will changed with the number of receivers.This problem does not exist in the method of Cross Ambiguity Function Mapping (CAF-MAP). However, conventional CAF-MAP method need initialized location of source. The computing efficiency is not good. In this paper, we propose a modified CAF-MAP method, which utilizes multiple grades lookup table to conquer above problems. We then extend the modified CAF-MAP method to the case of multiple sources localization. The CAFs from different sources will fold each other when sources are close which resulting several false peaks. We then propose a modified mapping approach to avoid this problem. Finally, computer simulations corroborate the theoretical results and the good performance of the proposed method. The rest of the paper is organized as follow.Chapter 2 investigates conventional method of source localization using TDOA and FODA measurements and analyses the defects in the process of localization.Chapter 3 proposes a modified CAF-MAP method for single source localization. The method then is extended to the case of multiple observed time segments. The proposed method conquers the defects of conversation CAF-MAP method.Chapter 4 extends the modified CAF-MAP to the case of multiple sources localization. CAFs from different sources will fold each other when they are close. This will result several false peaks. We then propose a modified mapping approach to avoid the problem.Finally, we construct a digital simulation system and simulate the proposed method using communication signals and radar signals respectively. Computer simulations corroborate the theoretical results and the good performance of the proposed method. The proposed method enriches the framework of passive localization, and strongly supports the passive localization engineering.