首页> 外国专利> Enhanced adaptive statistical filter providing sparse data stochastic mensuration for residual errors to improve performance for target motion analysis noise discrimination

Enhanced adaptive statistical filter providing sparse data stochastic mensuration for residual errors to improve performance for target motion analysis noise discrimination

机译:增强型自适应统计滤波器,可为残留误差提供稀疏的数据随机性保证,从而提高目标运动分析噪声识别的性能

摘要

An adaptive statistical filter system for receiving a data stream compris a series of data values from a sensor associated with successive points in time. Each data value includes a data component representative of the motion of a target and a noise component, with the noise components of data values associated with proximate points in time being correlated. The adaptive statistical filter system includes a prewhitener, a plurality of statistical filters of different orders, stochastic decorrelator and a selector. The prewhitener generates a corrected data stream comprising corrected data values, each including a data component and a time-correlated noise component. The plural statistical filters receive the corrected data stream and generate coefficient values to fit the corrected data stream to a polynomial of corresponding order and fit values representative of the degree of fit of corrected data stream to the polynomial. The stochastic decorrelator uses a spatial Poisson process statistical significance test to determine whether the fit values are correlated. If the test indicates the fit values are not randomly distributed, it generates decorrelated fit values using an autoregressive moving average methodology which assesses the noise components of the statistical filter. The selector receives the decorrelated fit values and coefficient values from the plural statistical filters and selects coefficient values from one of the filters in response to the decorrelated fit values. The coefficient values are coupled to a target motion analysis module which determines position and velocity of a target.
机译:用于接收数据流的自适应统计滤波器系统包括与连续时间点相关联的来自传感器的一系列数据值。每个数据值包括代表目标运动的数据分量和噪声分量,与邻近时间点关联的数据值的噪声分量相关。自适应统计滤波器系统包括预增白剂,多个不同阶的统计滤波器,随机去相关器和选择器。预增白剂产生包括校正后的数据值的校正后的数据流,每个校正后的数据值包括数据分量和与时间相关的噪声分量。多个统计滤波器接收校正后的数据流,并生成系数值以使校正后的数据流适合于相应阶次的多项式,并且拟合值表示校正后的数据流与多项式的适合度。随机去相关器使用空间泊松过程统计显着性检验来确定拟合值是否相关。如果测试表明拟合值不是随机分布的,则使用自回归移动平均方法生成去相关的拟合值,该方法评估统计滤波器的噪声成分。选择器从多个统计滤波器接收解相关的拟合值和系数值,并响应于解相关的拟合值从滤波器之一中选择系数值。系数值耦合到目标运动分析模块,该模块确定目标的位置和速度。

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