基于机场场面非视距信道建模的MLAT定位算法研究

Recently decade, multilateration(MLAT)has been proposed as an advanced technology for airport surface surveillance. The biggest problem MLAT system currently faces is the adverse effects of NLOS(None-line-of-sight) caused by airport surface's complex geography and electromagnetic environments. According to the typical characteristic of airport surface and based on MLAT measurement data of multiple airport surfaces, this project will construct NLOS channel model of medium and large-scale typical airport surface and a new location estimation algorithm will be designed in line with the motion characteristics of surface target. The main innovation points of this project are as follows: a NLOS channel model suitable to the medium and large-scale airport surface is constructed first time based on the MLAT measurement data(TDOA form,1090MHz). Two independent discrete-time Markov chains are used to model the transition of the target motion state and measurement state respectively and then are combined to form a compound Markov chain that is able to describe the uncertainty of motion-measurement joint state. In the algorithm design, multiple-model approach is applied for solving the motion state uncertainty and mitigating NLOS effects. Through creative works, we will propose the efficient solutions for related research. Furthermore, we will design a simulation platform to demonstrate the effectiveness of our solution and meantime prove it in real MLAT systems.

多点定位(MLAT)是近十余年来国际上提出的一种先进的机场场面监视技术。目前MLAT工程化系统所面临的最大难题是由机场场面复杂地理及电磁环境所引起的非视距(NLOS)的不利影响。本课题拟根据典型机场场面环境的特点，以多个机场场面MLAT实测数据为数据源，研究大中型典型机场场面下NLOS成分的信道模型，并结合场面目标的运动特性设计新的定位算法。本课题主要创新点有：在国内外首次根据实测数据建立大中型典型机场场面下的NLOS信道模型(TDOA形式，1090MHz)；两个独立的离散马尔科夫链被分别用来对目标运动状态及LOS/NLOS测量状态的切换建模；组合所构成的复合马尔科夫链被用来描述运动-测量联合状态的不确定性；多模型方法被用在定位算法设计中以便解决运动状态不确定性及消除NLOS的影响。本课题力争在相关研究中获得创新性成果并在仿真及实际MLAT系统中进行验证。

多点定位是一种新型的无源定位技术，可准确和鲁棒性地定位出飞行器的位置并加以识别，因此它能够代替二次雷达而成为下一代空管系统的基石；然而MLAT的实际定位效果受到多种不利因素的影响。针对传统MLAT系统定位算法的缺点，在结合了机场场面的特点后，提出了适合机场场面目标定位的一种新算法，极大地提高了场面目标的定位精度和鲁棒性；针对MLAT系统场面目标运动状态的检验特殊性，设计了一种与其定位算法相匹配的运动状态检验方法，有效地解决了该问题；针对常规TDOA状态方程的不足，结合已成熟的直角坐标系下的状态模型，推导出了一种TDOA状态模型方程，并基于该模型方程，设计了一种TDOA跟踪滤波器。与传统TDOA状态模型方程相比，所推导出状态模型方程和滤波器不但能提高TDOA的估计精度，还可更有效地消除NLOS成分。