Du Jianping, Wang Ding, Yu Wanting, Yu Hongyi
National Digital Switching System Engineering and Technological Research Center, Zhengzhou 450002, China.
Sensors (Basel). 2018 Mar 17;18(3):892. doi: 10.3390/s18030892.
A novel geolocation architecture, termed "Multiple Transponders and Multiple Receivers for Multiple Emitters Positioning System (MTRE)" is proposed in this paper. Existing Direct Position Determination (DPD) methods take advantage of a rather simple channel assumption (line of sight channels with complex path attenuations) and a simplified MUltiple SIgnal Classification (MUSIC) algorithm cost function to avoid the high dimension searching. We point out that the simplified assumption and cost function reduce the positioning accuracy because of the singularity of the array manifold in a multi-path environment. We present a DPD model for unknown signals in the presence of Multi-path Propagation (MP-DPD) in this paper. MP-DPD adds non-negative real path attenuation constraints to avoid the mistake caused by the singularity of the array manifold. The Multi-path Propagation MUSIC (MP-MUSIC) method and the Active Set Algorithm (ASA) are designed to reduce the dimension of searching. A Multi-path Propagation Maximum Likelihood (MP-ML) method is proposed in addition to overcome the limitation of MP-MUSIC in the sense of a time-sensitive application. An iterative algorithm and an approach of initial value setting are given to make the MP-ML time consumption acceptable. Numerical results validate the performances improvement of MP-MUSIC and MP-ML. A closed form of the Cramér-Rao Lower Bound (CRLB) is derived as a benchmark to evaluate the performances of MP-MUSIC and MP-ML.
本文提出了一种新颖的地理定位架构，称为“用于多发射源定位系统的多应答器和多接收器（MTRE）”。现有的直接位置确定（DPD）方法利用了相当简单的信道假设（具有复杂路径衰减的视距信道）和简化的多重信号分类（MUSIC）算法代价函数来避免高维搜索。我们指出，由于多径环境中阵列流形的奇异性，这种简化的假设和代价函数降低了定位精度。本文提出了一种存在多径传播时未知信号的DPD模型（MP-DPD）。MP-DPD添加了非负实路径衰减约束，以避免因阵列流形的奇异性而导致的错误。设计了多径传播MUSIC（MP-MUSIC）方法和活动集算法（ASA）来降低搜索维度。此外，还提出了一种多径传播最大似然（MP-ML）方法，以克服MP-MUSIC在时间敏感应用方面的局限性。给出了一种迭代算法和初始值设置方法，以使MP-ML的时间消耗可接受。数值结果验证了MP-MUSIC和MP-ML的性能提升。推导了克拉美罗下界（CRLB）的闭式作为评估MP-MUSIC和MP-ML性能的基准。
