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不完全随机有偏量测下高炮火控系统诸元误差统计特性分析 被引量:1

Shoot-element Error Statistical Characteristic Analysis for Antiaircraft Fire-control System with Incomplete and Stochastic-bias Measurements
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摘要 针对频繁出现于工程实际中的不完全随机有偏量测为背景的火控系统性能的理论研究,建立了不完全随机有偏量测下的离散线性观测系统数学模型,给出了观测系统统计意义下的估计误差方差Cramér-Rao下界(CRLB);根据目标位置、速度与射击诸元间的非线性误差传递关系,利用U-T变换得到不完全随机有偏量测影响下的射击诸元误差方差下界。以某型数字化高炮火控系统为例,仿真结果表明:在给定探测概率和偏差发生率影响下,观测系统在标准航路特征点上的估计性能较无偏完全量测的估计性能下降23.3%,导致火控系统性能下降25%. In order to study fire control system performance based on incomplete and stochastic-bias measurements in practical engineering. A discrete-time linear observation system model and estimation error variance characteristic Cram6r-Rao lower bound (CRLB) were proposed; considering the non-linear error propagation relations from target location to hit point, shoot-element error variances statistical CRLB with incomplete and stochastic-bias measurement was obtained by the U-T transform. The optimal performance index was calculated by a certain type digital antiaircraft fire-control system with given detection probability and bias occurrence probability. The simulated results show that the estimation performance of the observation system decreases by 23.3% compared with complete and unbiased measurements at a certain characteristic point, and the performance of the fire-control system decreases by 25%.
作者 刘锐 盛安冬
出处 《兵工学报》 EI CAS CSCD 北大核心 2010年第2期229-234,共6页 Acta Armamentarii
基金 国家自然科学基金资助项目(60804019)
关键词 自动控制技术 高炮 不完全量测 随机有偏量测 Cramér-Rao下界 automatic control technology antiaircraft incomplete measurement stochastic-bias measurement Cramer-Rao lower bound
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  • 1Passerieux J M, Van Cappel D. Optimal observer maneuver for bearings-only tracking [ J]. IEEE Trans on Aerosp and Electron Syst, 1998, 34(3) : 777 -788.
  • 2Tichavsky P, Muravchik C H, Nehorai A. Posterior Cramer-Rao bounds for discrete-time nonlinear filtering [ J ]. IEEE Trans on Signal Processing, 1998, 46(5 ) : 1386 - 1396.
  • 3Hernandez M, Kirubarajan T, Bar-Shalom Y. Muhisensor resource deployment using posterior Cramer-Rao bounds [J]. IEEE Trans on Aerospace and Electronic Systems, 2004, 40 (2) : 399 - 416.
  • 4Xiong K, Zhang H Y, Chan C W. Performance evaluation of UKF-based nonlinear filtering [ J ]. Automatica, 2006, 42 ( 2 ) : 261 - 270.
  • 5Xu Ben-lian, Wu Zheng-yi, Wang Zhi-quan. On the Cramer-Rao lower bound for biased bearings-only maneuvering target tracking [J]. Signal Processing, 2007, 87 (12) : 3175 - 3189.
  • 6Nahi N E. Optimal recursive estimation with uncertain observation [J]. IEEE Trans on Inform Theory, 1969, 15(7) : 457 -462.
  • 7Farina A, Ristic B, Timmoneri L. Cramrr-Rao bound for nonlinear filtering with and its application to target tracking [J] IEEE Trans on Signal Processing, 2002, 50 (8) : 1916 - 1924.
  • 8Hernandez M, Ristic B, Farina A, et al. A comparison of two Cramer-Rao bounds for nonlinear filtering withe [J]. IEEE Trans on Signal Processing, 2004,52 (9) : 2361-2369.
  • 9Van Trees H. Detection, estimation, and modulation theory, part Ⅰ[M]. New York:Wiley, 1968.
  • 10Mallick M, Scala B F L, Arulampalam S. Differential geometry measures of nonlinearity for the bearing-only tracking problem [ C ] //Proceedings of SPIE Conference on Signal Processing, Sensor Fusion and Target Recognition, US: Orlando FL, 2005: 288 - 300.

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