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Initialization and tracking using Doppler-biased multistatic time-of-arrival measurements with linear frequency modulated waveforms

机译:使用多普勒偏置多静态到达时间测量和线性调频波形进行初始化和跟踪

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We investigate the target tracking problem in a multistatic sensor configuration in which the system uses Doppler tolerant waveforms (DTW), specifically the linear frequency modulated (LFM or chirp) waveforms, for target illumination. DTW introduce a bias to the true time-of-arrival (TOA), as a result of which the corresponding range measurement accuracy is degraded when this bias is ignored. It might be thought that with N sensors measuring the time delays (which have different combinations of range and range rate vectors) one would have complete observability from a single frame. However, N such measurements do not yield the desired observability regardless of N and the sensor geometry. An important part in the design of a tracking filter using nonlinear measurements is the initialization: the initial state estimate should be unbiased and the associated covariance should be consistent with the errors. This paper presents a maximum likelihood based method as well as a simpler iterative bias cancellation method to estimate the target initial state from two observation frames. The iterative method makes it possible to obtain unbiased initial position and velocity estimates by canceling out the Doppler bias. Simulation results confirm that both estimators are efficient and the filter initialized by either estimator is statistically consistent. We also analyze the effect of the range-Doppler coupling coefficient on the performance of the filter. As is so often the case, the positive coefficient (which corresponds to upsweep) is shown to be superior to the negative one (downsweep).
机译:我们研究了多静态传感器配置中的目标跟踪问题,在该配置中,系统使用多普勒容忍波形(DTW),特别是线性频率调制(LFM或线性调频)波形来进行目标照明。 DTW对实际到达时间(TOA)引入了偏差,因此,当忽略该偏差时,相应的距离测量精度会降低。可以认为,使用N个传感器测量时间延迟(具有不同的距离和距离率矢量组合),一个传感器就可以从单个帧中完全观察到。但是,无论N和传感器的几何形状如何,N次这样的测量都不会产生所需的可观察性。使用非线性测量的跟踪滤波器设计中的一个重要部分是初始化:初始状态估计应无偏见,并且相关的协方差应与误差一致。本文提出了一种基于最大似然的方法以及一种更简单的迭代偏差消除方法,用于从两个观测帧中估计目标初始状态。迭代方法可以通过抵消多普勒偏差来获得无偏差的初始位置和速度估计值。仿真结果证实了两个估计器都是有效的,并且由任何一个估计器初始化的滤波器在统计上都是一致的。我们还分析了距离多普勒耦合系数对滤波器性能的影响。通常情况下,正系数(对应于上扫频)显示为优于负系数(下扫频)。

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