High-Precision Joint TDOA and FDOA Location System
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 utiliz...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/16/4/693 |
| _version_ | 1797297055704547328 |
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| author | Guoyao Xiao Qianhui Dong Guisheng Liao Shuai Li Kaijie Xu Yinghui Quan |
| author_facet | Guoyao Xiao Qianhui Dong Guisheng Liao Shuai Li Kaijie Xu Yinghui Quan |
| author_sort | Guoyao Xiao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-07T22:15:42Z |
| format | Article |
| id | doaj.art-287a4d1d260b4e33abce56894e0c510d |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-07T22:15:42Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-287a4d1d260b4e33abce56894e0c510d2024-02-23T15:33:07ZengMDPI AGRemote Sensing2072-42922024-02-0116469310.3390/rs16040693High-Precision Joint TDOA and FDOA Location SystemGuoyao Xiao0Qianhui Dong1Guisheng Liao2Shuai Li3Kaijie Xu4Yinghui Quan5Department of Remote Sensing Science and Technology, Xidian University, Xi’an 710071, ChinaHangzhou Institute of Technology, Xidian University, Hangzhou 311231, ChinaNational Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, ChinaInstitute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing 100094, ChinaSchool of Electronic Engineering and the Key Laboratory of Collaborative Intelligence Systems, Ministry of Education, Xidian University, Xi’an 710071, ChinaDepartment of Remote Sensing Science and Technology, Xidian University, Xi’an 710071, ChinaPassive 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.https://www.mdpi.com/2072-4292/16/4/693TDOA/FDOAcross-ambiguity functionquadric surface fittingreal-time signal processing |
| spellingShingle | Guoyao Xiao Qianhui Dong Guisheng Liao Shuai Li Kaijie Xu Yinghui Quan High-Precision Joint TDOA and FDOA Location System Remote Sensing TDOA/FDOA cross-ambiguity function quadric surface fitting real-time signal processing |
| title | High-Precision Joint TDOA and FDOA Location System |
| title_full | High-Precision Joint TDOA and FDOA Location System |
| title_fullStr | High-Precision Joint TDOA and FDOA Location System |
| title_full_unstemmed | High-Precision Joint TDOA and FDOA Location System |
| title_short | High-Precision Joint TDOA and FDOA Location System |
| title_sort | high precision joint tdoa and fdoa location system |
| topic | TDOA/FDOA cross-ambiguity function quadric surface fitting real-time signal processing |
| url | https://www.mdpi.com/2072-4292/16/4/693 |
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