Qu Fu-Yong, Meng Xiang-Wei. Source Localization Using TDOA and FDOA Measurements Based on Constrained Total Least Squares Algorithm[J]. Journal of Electronics & Information Technology, 2014, 36(5): 1075-1081. doi: 10.3724/SP.J.1146.2013.01019
Citation:
Qu Fu-Yong, Meng Xiang-Wei. Source Localization Using TDOA and FDOA Measurements Based on Constrained Total Least Squares Algorithm[J]. Journal of Electronics & Information Technology, 2014, 36(5): 1075-1081. doi: 10.3724/SP.J.1146.2013.01019
Qu Fu-Yong, Meng Xiang-Wei. Source Localization Using TDOA and FDOA Measurements Based on Constrained Total Least Squares Algorithm[J]. Journal of Electronics & Information Technology, 2014, 36(5): 1075-1081. doi: 10.3724/SP.J.1146.2013.01019
Citation:
Qu Fu-Yong, Meng Xiang-Wei. Source Localization Using TDOA and FDOA Measurements Based on Constrained Total Least Squares Algorithm[J]. Journal of Electronics & Information Technology, 2014, 36(5): 1075-1081. doi: 10.3724/SP.J.1146.2013.01019
The two-stage Weighted Least Squares (WLS) method is a well-known linear approach in Time- Difference-Of-Arrival (TDOA) and Frequency-Difference-Of-Arrival (FDOA) passive localization. But this method can only attain the CRLB in a modest noise environment and the bias of the localization result is significant for strong noise. This paper discusses a Constrained Total Least Square (CTLS) solution to the pseudo linear equations with two constrains for TDOA/FDOA localization. A unified expression for several LS solutions is derived based on Lagrange multiplier. The Constrained Weighted Least Square (CWLS) method and Constrained Least Square (CLS) localization method reduce to the special cases of the localization solution. The simulation results show that the proposed method has lower Mean Square Error (MSE) and lower bias compared with the two-stage WLS method, and it is more robust to noise.