High-Precision Joint TDOA and FDOA Location System

Author:

Xiao Guoyao123ORCID,Dong Qianhui4ORCID,Liao Guisheng5,Li Shuai6,Xu Kaijie7,Quan Yinghui123

Affiliation:

1. Department of Remote Sensing Science and Technology, Xidian University, Xi’an 710071, China

2. Xi’an Key Laboratory of Advanced Remote Sensing, Xi’an 710071, China

3. Key Laboratory of Collaborative Intelligence Systems, Ministry of Education, Xidian University, Xi’an 710071, China

4. Hangzhou Institute of Technology, Xidian University, Hangzhou 311231, China

5. National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

6. Institute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing 100094, China

7. School of Electronic Engineering and the Key Laboratory of Collaborative Intelligence Systems, Ministry of Education, Xidian University, Xi’an 710071, China

Abstract

Passive location based on TDOA (time difference of arrival) and FDOA (frequency difference of arrival) is the mainstream method for target localization. This paper proposes a fast time–frequency difference positioning method to address issues such as low accuracy, large computational resource utilization, and limited suitability for real-time signal processing in the conventional CAF (cross-ambiguity function)-based approach, aiming to complete the processing of the target radiation source to obtain the target parameters within a short timeframe. In the mixing product operation step of the CAF, a frequency-domain approach replaces the time-domain convolution operation in PW-ZFFT (pre-weighted Zoom-FFT) to reduce the computational load of the CAF. Additionally, a quadratic surface fitting method is used to enhance the accuracy of TDOA and FDOA. The localization solution is obtained using Newton’s method, which can provide more accurate results compared to analytical methods. Next, a signal processing platform is designed with FPGA (field-programmable gate array) and multi-core DSP (digital signal processor), and works by dividing and mapping the algorithm functional modules according to the hardware’s characteristics. We analyze the architectural advantages of multi-core DSP and design methods to improve program performance, such as EDMA transfer optimization, inline function optimization, and cache optimization. Finally, this paper constructs simulation tests in typical positioning scenarios and compares them to hardware measurement results, thus confirming the correctness and real-time capability of the program.

Funder

National Natural Science Foundation of China

Science Funds for Distinguished Young Scholars of Shaanxi Province

Publisher

MDPI AG

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