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基于正則化約束總體最小二乘的單站DOA-TDOA無(wú)源定位算法

趙擁軍,  趙勇勝,  趙闖

趙擁軍, 趙勇勝, 趙闖. 基于正則化約束總體最小二乘的單站DOA-TDOA無(wú)源定位算法[J]. 電子與信息學(xué)報(bào), 2016, 38(9): 2336-2343. doi: 10.11999/JEIT151379
引用本文: 趙擁軍, 趙勇勝, 趙闖. 基于正則化約束總體最小二乘的單站DOA-TDOA無(wú)源定位算法[J]. 電子與信息學(xué)報(bào), 2016, 38(9): 2336-2343. doi: 10.11999/JEIT151379
ZHAO Yongjun, ZHAO Yongsheng, ZHAO Chuang. Single-observer Passive DOA-TDOA Location Based on Regularized Constrained Total Least Squares[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2336-2343. doi: 10.11999/JEIT151379
Citation: ZHAO Yongjun, ZHAO Yongsheng, ZHAO Chuang. Single-observer Passive DOA-TDOA Location Based on Regularized Constrained Total Least Squares[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2336-2343. doi: 10.11999/JEIT151379

基于正則化約束總體最小二乘的單站DOA-TDOA無(wú)源定位算法

doi: 10.11999/JEIT151379 cstr: 32379.14.JEIT151379
基金項(xiàng)目: 

國(guó)家自然科學(xué)基金(61401469, 41301481, 61501513)，國(guó)家高技術(shù)研究發(fā)展計(jì)劃(2012AA7031015)

Single-observer Passive DOA-TDOA Location Based on Regularized Constrained Total Least Squares

Funds: 

The National Natural Science Foundation of China (61401469, 41301481, 61501513), The National High Technology Research and Development Program of China (2012AA7031015)

  • 摘要: 針對(duì)利用單站外輻射源的目標(biāo)無(wú)源定位問(wèn)題，該文提出一種聯(lián)合到達(dá)角度和時(shí)差信息的正則化約束總體最小二乘(RCTLS)定位算法。首先，將非線(xiàn)性的到達(dá)角度和時(shí)差的觀測(cè)方程進(jìn)行線(xiàn)性化處理，分析了方程系數(shù)矩陣可能出現(xiàn)的病態(tài)問(wèn)題，將定位問(wèn)題建立為RCTLS模型，并采用牛頓迭代方法對(duì)模型求解，從而得到目標(biāo)位置估計(jì)。最后，推導(dǎo)了算法的理論誤差，并按照均方誤差最小的原則推導(dǎo)了正則化參數(shù)的最優(yōu)值。仿真結(jié)果表明，算法的定位精度和魯棒性均優(yōu)于約束總體最小二乘(CTLS)算法。此外，對(duì)系統(tǒng)幾何精度因子圖的分析表明，目標(biāo)及外輻射源的位置對(duì)定位精度也有影響。
    Abstract: To solve the single-observer passive location estimation using illuminators of opportunity, a jointing Direction Of Arrival (DOA) and Time Difference Of Arrival (TDOA) location method based on Regularized Constrained Total Least Squares (RCTLS) algorithm is proposed. Firstly, the DOA and TDOA measurement equations are linearized. Considering the errors in the location equations, the localization problem is established as a RCTLS model. Then the Newtons method is applied to solving the RCTLS model to obtain the target position. The theoretical error of the proposed algorithm is derived and an optimal regularization parameter is chosen by the least mean square error rule. Simulation results show that the proposed RCTLS algorithm has lower mean squares error than the Constrained Total Least Squares (CTLS) algorithm. Moreover, from the Geometric Dilution Of Precision (GDOP) figure, it can be concluded that positions of the target and illuminators are also important factors affecting the localization accuracy.
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出版歷程
  • 收稿日期:  2015-12-08
  • 修回日期:  2016-04-27
  • 刊出日期:  2016-09-19

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