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首页> 外文期刊>IEEE Transactions on Aerospace and Electronic Systems >Radar measurement noise variance estimation with several targets of opportunity
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Radar measurement noise variance estimation with several targets of opportunity

机译：具有多个机会目标的雷达测量噪声方差估计

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摘要

A number of methods exist to track a target's uncertain motion through space using inherently inaccurate sensor measurements. A powerful method of adaptive estimation is the interacting multiple model (IMM) estimator. In order to carry out state estimation from the noisy measurements of a sensor, however, the filter should have knowledge of the statistical characteristics of the noise associated with that sensor. The statistical characteristics (accuracies) of real sensors, however, are not always available, in particular for legacy sensors. A method is presented of determining the measurement noise variances of a sensor, assumed to be constant, by using multiple IMM estimators while tracking targets whose motion is not known-targets of opportunity. Combining techniques outlined in (Bar-Shalom et al., 2001) and (Gauvrit, 1984), the likelihood functions are obtained for a number of IMM estimators, each with different assumptions on the measurement noise variances. Then a search is carried out over a varying grid of IMMs to bracket the variances of the sensor measurement noises. The end result consists of estimates of the measurement noise variances of the sensor in question.
机译：存在许多使用固有不准确的传感器测量值来跟踪目标在空间中不确定运动的方法。自适应估计的一种有效方法是交互多模型（IMM）估计器。但是，为了从传感器的噪声测量值进行状态估计，滤波器应了解与该传感器相关的噪声的统计特性。但是，并非总是可以使用真实传感器的统计特性（准确性），尤其是对于传统传感器而言。提出了一种方法，该方法通过使用多个IMM估计器同时跟踪运动未知的机会目标来确定假定为恒定的传感器的测量噪声方差。结合（Bar-Shalom et al。，2001）和（Gauvrit，1984）中概述的技术，获得了许多IMM估计器的似然函数，每个估计器在测量噪声方差上都有不同的假设。然后，在变化的IMM网格上进行搜索，以包围传感器测量噪声的变化。最终结果包括所讨论传感器的测量噪声方差的估计值。

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