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1.
针对单星仅测角对目标跟踪误差较大和不良测量条件下跟踪精度下降的问题,提出利用编队卫星对非合作目标进行联合跟踪的方法。采用考虑地球非球形J2引力摄动的轨道动力学模型,建立多视线测量模型,融合编队卫星对目标的观测数据。然后,基于新息设计增益调节矩阵提高滤波器在测量故障条件下的鲁棒性。最后,建立仿真模型进行验证。仿真结果表明,相比单星跟踪,该方法的位置误差和速度误差分别减少了27.06%和26.96%。在系统存在异常量测时,相比常规滤波,该方法也具有更高的精确性和更好的鲁棒性。 相似文献
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Tracking problem in spherical coordinates with range rate (Doppler) measurements, which would have errors correlated to the range measurement errors, is investigated in this paper. The converted Doppler measurements, constructed by the product of the Doppler measurements and range measurements, are used to replace the original Doppler measurements. A de-noising method based on an unbiased Kalman filter (KF) is proposed to reduce the converted Doppler measurement errors before updating the target states for the constant velocity (CV) model. The states from the de-noising filter are then combined with the Cartesian states from the converted measurement Kalman filter (CMKF) to produce final state estimates. The nonlinearity of the de-noising filter states are handled by expanding them around the Cartesian states from the CMKF in a Taylor series up to the second order term. In the mean time, the correlation between the two filters caused by the common range measurements is handled by a minimum mean squared error (MMSE) estimation-based method. These result in a new tracking filter, CMDN-EKF2. Monte Carlo simulations demonstrate that the proposed tracking filter can provide efficient and robust performance with a modest computational cost. 相似文献
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In this paper, the optimal robust non-fragile Kalman-type recursive filtering problem is studied for a class of uncertain systems with finite-step autocorrelated measurement noises and multiple packet dropouts. The system state, measurement output and filter parameters are all subject to stochastic uncertainties or multiplicative noises, where the measurement noises are finite-step autocorrelated. When there exist multiple packet dropouts in the system output, the original system is converted into an auxiliary stochastic uncertain system by the augmentation of system states and measurements. The process noises and measurement noises of the auxiliary system are shown to be finite-step autocorrelated and cross-correlated. Then, a robust non-fragile Kalman-type recursive filter is designed that is optimal in the minimum-variance sense. The proposed filter is not only robust against the uncertainties in the system model and measurement model, but also non-fragile against the implementation error with the filter parameters. Simulation results are employed to demonstrate the effectiveness of the proposed method. 相似文献
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A reduced state estimator is derived for systems with bounded parameters as inputs. Optimal filter gains are derived for minimizing the total covariance of the estimation error due to measurement noise and parameter uncertainty. It is shown that these filter gains for a two-state system with a Gaussian parameter satisfy the Kalata relation in steady state. Equations are also derived for optimally filtering measurements in arbitrary time order. This reduced state estimator offers novelties over a traditional Kalman filter in its application to the class of problems considered. The total error covariance, which is minimized, makes no use of plant noise. Furthermore, the filter is easier to optimize in high dimensional and multiple sensor applications as well as in processing out-of-sequence measurements. 相似文献
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This paper is concerned with the adaptive robust cubature Kalman filtering problem for the case that the dynamics model error and the measurement model error exist simultaneously in the satellite attitude estimation system. By using Hubel-based robust filtering methodology to correct the measurement covariance formulation of cubature Kalman filter, the proposed filtering algorithm could effectively suppress the measurement model error. To further enhance this effect and reduce the impact of the dynamics model error, two different adaptively robust filtering algorithms, one with the optimal adaptive factor based on the estimated covariance matrix of the predicted residuals and the other with multiple fading factors based on strong tracking algorithm, are developed and applied for the satellite attitude estimation. The quaternion is employed to represent the global attitude parameter, and three-dimensional generalized Rodrigues parameters are introduced to define the local attitude error. A multiplicative quaternion error is derived from the local attitude error to maintain quaternion normalization constraint in the filter. Simulation results indicate that the proposed novel algorithm could exhibit higher accuracy and faster convergence compared with the multiplicative extended Kalman filter, the unscented quaternion estimator, and the adaptive robust unscented Kalman filter. 相似文献
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The three-dimensional (3D) converted measurements filtering (CMF) with both converted position and raw range-rate measurement is proposed to solve the Doppler radar target tracking, where the error between radar-target range and range rate are correlated. Firstly, not using pseudomeasurement constructed by product of range and range rate to reduce the high nonlinearity, the raw range-rate measurements are utilized by unscented Kalman filter (UKF), where the converted errors of the position and the range rate are decorrelated, then linear part (position measurements) and nonlinear part (range-rate measurement) are sequentially processed by Kalman filter (KF) and UKF. Secondly, based on the assumption of small measurement error, the mean and covariance of converted measurement errors are derived by second-order Taylor series expansion. Finally, the influence of the correlated coefficient rho between the range and range rate, and the range-rate noise deviation sigmar are taken into account and extreme values of rho and sigmar are used in Monte Carlo simulations. The results show that the proposed method is, in a sense, effective and practical 相似文献
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The continued development of the symmetric measurement equation (SME) filter for track maintenance in multiple target tracking (MTT) is considered, focusing on the case in which the SMEs are generated by forming sums of products of the original position measurements. The SME filter is developed for the case of N targets whose motions consist of random perturbations about constant-velocity trajectories. It is assumed that measurements of x -coordinate positions are available, and that the number of measurements is equal to the number of targets. Various analytical properties of the SME filter are studied. It is shown that under a very weak condition, the estimation error equation is locally exponentially stable. The performance of the SME filter is investigated by comparing it with an optimal (minimum-variance) estimator and by generating a computer simulation in the six-target case 相似文献
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为了解决大场景下基于三维到达角的目标跟踪问题,提出了一种具有无偏性的伪线性卡尔曼滤波。首先,基于三维到达角信息对目标运动模型与量测模型进行建模;之后,对量测模型进行了伪线性化处理,得到了线性形式的目标量测模型。为了解决伪线性卡尔曼滤波存在的有偏性问题,提出了一种结合EKF(extend Kalman filter)的三维伪线性无偏卡尔曼滤波。仿真实验表明,该模型能够对非机动目标与机动目标有效跟踪,对于百公里级别的目标,当角测量误差从0.1°变化到0.5°,算法在仿真时间结束时均能将绝对位置误差降低至10 km以内,且算法的运行速度与EKF为同一个量级,同时兼顾了抗干扰能力、定位跟踪精度、运行效率的要求,能够为大场景下的目标跟踪提供有效方法。 相似文献
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An optimal reduced-order observer-estimator (filter) is developed which can provide a full-dimensional vector of state estimates for systems where the dimension of the measurement vector is smaller than that of the state vector and none of the measurements are noise free. The reduced-order filter consists of two subfilters each of which provides a subset of the optimal estimate. A two-step L -K transformation is employed to minimize the estimate error variance of each subfilter. The optimal reduced-order filter developed is computationally efficient 相似文献
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Cloutier J.R. Lin C.-F. Yang C. 《IEEE transactions on aerospace and electronic systems》1993,29(3):786-797
An enhancement of the variable dimension (VD) filter for maneuvering-target tracking is presented. The use of measurement concatenation, a procedure whereby fast sampled measurements are stacked while maintaining their proper relationships with the states, leads to significant reduction in estimation error by low processing rate algorithms. The use of double decision logic (DDL) for the maneuver onset and ending detection as well as appropriate procedures for reinitialization of the estimation filters results in improved maneuver detection and filter adaptation. Simulation results show the performance of the proposed enhanced variable dimension (EVD) filter 相似文献
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视线矢量观测是实现自主导航的重要方式。本文针对单位矢量的加法观测模型中观测矢量非单位化问题和乘法观测模型中测量噪声与实际情况不符的问题,提出二次旋转乘法观测模型。通过真实矢量在正交方向上进行的两次刚体旋转,获得了与现有乘法观测模型形式相同、但旋转角服从瑞利分布的正确观测方程。推导了测量误差的统计特性和双矢量观测的性质,并从空间几何角度给予了解释。数值仿真结果表明,二次旋转乘法观测模型弥补了由加法观测模型线性化所引起的问题,具有更精确的误差形式,由此给出了模型的潜在应用范围。 相似文献
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在以前的研究中,无偏转测量误差协方差阵是基于当前测量值得到的.为了能利用所有历史数据以得到更精确的转换测量误差协方差阵估计,文中在均方意义下,推导了三维雷达的最优无偏转换测量误差协方差阵. 相似文献
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在传统Kalman滤波中,卡方检测方法简单地将量测划分为正常和异常两种,针对其不足之处,改进并提出了一种新的软卡方检测方法。新方法根据卡方检测结果构造连续变化的量测,利用权重系数,充分挖掘处于正常值与异常值之间的可疑量测新息,同时还将该方法推广成多维量测的多分量卡方检测形式,建立了全面完整的软卡方检测Kalman滤波量测更新方程。最后,通过惯导/卫导组合导航仿真,验证了软卡方检测Kalman滤波的优势:无需任何参数调整且具有比Sage-Husa自适应滤波更小的统计误差波动。 相似文献
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Shertukde H.M. Bar-Shalom Y. 《IEEE transactions on aerospace and electronic systems》1991,27(4):582-592
The authors present an algorithm for the tracking of crossing targets using the centroid measurement and the centroid offset measurement of the distributed image formed by the targets. The measurements are obtained by a forward-looking infrared (FLIR) imaging sensor. The joint probabilistic data association merged-measurement coupled filter (JPDAMCF) is used for state estimation which performs filtering in a coupled manner for the targets with common measurements. Two filters are examined: one assuming the displacement noise white and the other one modeling it correctly as autocorrelated. The latter is shown to yield substantially better performance. The proposed algorithm demonstrates the usefulness of the JPDAMCF for tracking crossing targets in combination with the models for the centroid and offset measurements. Even though the centroid offset measurement requires more computations and a more complex model for estimation, it yields significantly better results if the filter accounts for its colored measurement noise 相似文献
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In a pico-satellite with small volume, measurements from on-board three-axis magnetometer (TAM) are not accurate, as it can be easily disturbed by other electronic systems. To improve its accuracy, a scheme of compensation methods is introduced in this article. The scheme is based on an improved measurement model of pico-satellite TAM, and it mainly consists of three steps. First, in satellite design stage, several techniques are recommended to simplify the afterwards compensations. Then after satellite assembly, TAM ground tests and pre-launch calibration with least-square batch filter are introduced to improve magnetometer performance. At the end, a post-launch calibration with unscented Kalman filter (UKF) is implemented with in-orbit data. The compensation scheme is used in the development of Chinese pico-satellite ZDPS-1A made by Zhejiang University. Results show that with the introduced compensation scheme, the maximum error of ZDPS-1A TAM can be reduced from 80 mG to 6 mG (1 G=10-4 T). 相似文献