高低轨双星时频差无源定位精度

高低轨卫星联合定位是提高地面辐射源无源定位精度的有效方法。从时差基线、速度差增加方面分析了高低轨双星定位精度相对同轨卫星定位精度高的原因,推导出高低轨双星时频差定位误差分布表达式,分析了高低轨联合定位适用的时频差测量方法及其测量精度。仿真分析结果表明:在低轨卫星星下点附近较大范围内,定位精度达到百米量级。验证了双星相对位置变化、时频差测量误差、高低轨卫星自身位置速度测量误差等因素对高低轨双星定位精度的影响。     

二阶和四阶互模糊函数在工程中的时频性能比较

利用两种方法,即模糊函数和四阶累积量模糊函数对目标的两个主要参量TDOA(time-delay of arrival)和FDOA(frequency - delay of arrival)进行理论上精确的推导和实际应用中在工程上的估计,并且指出了两种方法在理论与实际应用中所得到的两种几乎截然不同的结果,并对其加以详细的分析,阐明了这种矛盾的根源之所在,并由给出的仿真结果对上述结论加以说明.     

基于TDOA/FDOA不相关估计的选择融合定位方法

为提高单独到达时差或频差定位精度,本文首先提出可达TDOA克拉美罗界的TDOA解析解,然后采用最大似然网格搜索算法获得FDOA定位解,最后采用基于TDOA/FDOA不相关估计选择融合的解形成联合解。仿真和理论分析表明:该联合算法定位性能优于单独定位,定位精度在有或无地球约束时均可达联合的克拉美罗界。     

Approximate Maximum Likelihood Algorithm for Moving Source Localization Using TDOA and FDOA Measurements

 A closed-form approximate maximum likelihood (AML) algorithm for estimating the position and velocity of a moving source is proposed by utilizing the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements of a signal received at a number of receivers. The maximum likelihood (ML) technique is a powerful tool to solve this problem. But a direct approach that uses the ML estimator to solve the localization problem is exhaustive search in the solution space, and it is very computationally expensive, and prohibits real-time processing. On the basis of ML function, a closed-form approximate solution to the ML equations can be obtained, which can allow real-time implementation as well as global convergence. Simulation results show that the proposed estimator achieves better performance than the two-step weighted least squares (WLS) approach, which makes it possible to attain the Cram閞-Rao lower bound (CRLB) at a sufficiently high noise level before the threshold effect occurs.     

利用二星TDOA和FDOA测量及辅助高度信息对地面目标的定位算法及精度分析

卫星探测定位系统对地面辐射源目标定位时,一般利用TDOA(到达时间差)测量,而当辐射源与卫星之间存在相对运动时,也可以测量FDOA(到达频率差).当辐射源的高程已知时,可以利用WGS-84地球椭圆模型作为精确定位模型.据此提出了利用两颗低轨卫星的TDOA及FDOA测量对地面辐射源定位算法,并对定位的算法进行深入的研究,同时推导了定位误差的分布模型.