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为准确估计捷联导引头视线角速率,建立了全捷联导引头数学模型,根据弹目运动相对关系进行视线角速率解耦与估计算法研究。首先,建立了全捷联导引头数学模型,并利用Taylor 级数对其进行线性化;接着,根据弹目运动几何学与坐标系相对关系推导视线角速率解耦算法;然后,针对捷联导引头无法直接测量体视线角速率的问题,提出微分+稳态Kalman 滤波方法估计体视线角速率;最后,建立视线角速率解耦与估计算法验证系统并进行仿真实验,结果表明:解耦算法绝对误差小于510-5 rad/s,相对误差小于0.3%,验证了解耦算法的正确性;在包含导引头数学模型的条件下,采用角频率为19.2 rad/s 的稳态Kalman 滤波器,视线角速率估计误差小于410-3 rad/s,较直接微分方法的估计误差提高近一个量级。视线角速率解耦与估计算法同时能满足制导系统对精度与动态性能的要求。 相似文献
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We address the problem of adaptive time delay estimation with noisy measurements. We develop a computationally efficient adaptive time delay estimator based on Explicit time delay estimation (ETDE) algorithm, by applying the unbiased impulse response estimation ap-proach. In this algorithm, a weighted error function is de-rived, and the time delay is explicitly parameterized in the filter coefficients and iteratively updated directly by uti-lizing the modified error function. Simulations validate the performance of the proposed algorithm for colored input and low signal-to-noise ratio scenarios. 相似文献
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在室内行人导航中,为获取精确的航向角,提出了一种基于二阶插值滤波的航向估计算法。该算法通过建立四元数姿态运动测量模型,采用二阶插值滤波对陀螺仪、加速计和磁强计的测量数据进行数据融合,实现航向角解算,以过程噪声和测量噪声为设计参数,构造自适应噪声协方差矩阵,实现协方差误差估计最小化。通过对行走长方形参考路径得到的数据进行处理,加速计和磁强计组合与陀螺仪航向估计算法动态误差分别为13.6°和6.9°,采用二阶插值滤波航向估计算法后动态误差为2.3°。实验结果表明,该算法有效提高了航向估计的精度,减小了陀螺仪漂移、载体的线性加速度和周围局部磁场干扰对航向估计的影响。 相似文献
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Evoked potentials measured with scalp electrodes are often described as a deterministic process corrupted by unrelated noise. The common procedure to determine the signal is to average N repetitive measurements. By obtaining additional information from the N measurements, signal detection can be improved. An algorithm that estimates the signal autocorrelation from N given measurements is proposed. The estimator is consistent and unbiased, and its variance tends to 0 as o(N). Two filters that are applied to the average response are introduced. Both depend on the estimation of the signal and the noise autocorrelations. One filter is based on the assumption that the average response is a stationary process. The second filter coefficients are obtained by minimizing the mean squared error (MSE) of an optimal filter of a nonstationary process applied on a single sweep. When a small number of sweeps are averaged, the stationary assumption is adequate, and the MSE of the stationary optimal filter is two to five times less than the MSE of the average response. When a large number of measurements are considered, the error in estimating the autocorrelations decreases. In this case, applying the optimal filter for a nonstationary process leads to a significant improvement in the signal estimation. 相似文献
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针对在初始先验信息缺失时磁性目标滤波跟踪方法发散问题进行研究,本文提出了一种多初值模型的解决框架,并以平方根形式的中心差分卡尔曼滤波器(Square-Root Central Difference Kalman Filter,SRCDKF)为例,结合多初值模型得到了SRCDKF自适应磁性目标跟踪算法.文章首先根据远距离磁偶极子的磁场等效性,建立了多初值滤波跟踪模型,然后基于最大似然选择理论推导了如何从多模型中选择最佳结果,即多初值模型的选择方法,最后以SRCDKF滤波器为滤波单元,得到了基于SRCDKF的自适应磁性目标跟踪算法.经过仿真试验表明:(1)多初值模型建立和选择方法的有效性;(2)基于SRCDKF的自适应磁性目标跟踪算法,在初始位置信息缺失的情况下,能够有效完成对磁性目标的跟踪;(3)以不同滤波器为滤波单元的自适应跟踪算法跟踪试验结果表明,多初值模型的解决框架可解决初值先验未知下的跟踪问题. 相似文献
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锂电池及其应用近年来逐渐成为研究热点。以提高电池管理系统(BMS)对电池荷电状态(SOC)和健康状态(SOH)的估算精确度为目标,在建立二阶Thevenin等效电路模型基础上提出一种能在线协同估算电池荷电状态和健康状态的改进扩展卡尔曼滤波算法。通过分阶段脉冲放电实验,并利用最小二乘法求得模型参数。在动态应力测试工况(DST)下借助Matlab对比分析了改进扩展卡尔曼算法在SOC和SOH估计精确度、错误初值时算法收敛性、算法复杂度等方面的性能。实验表明,利用该算法可以精确估计出各采样点处的SOC和SOH,误差低于1%;且在初值不准确情况下,运行算法可快速收敛至真值附近,算法估算结果的准确性与模型参数的微调无关,鲁棒性较好。 相似文献
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提出了一种基于并行卡尔曼滤波的递推最小二乘算法.利用最小二乘算法对卡尔曼滤波的并行多路收敛输出值进行二次优化估计.将本算法应用于正弦波测频,与只采用卡尔曼滤波的算法相比,可使频率估计精度得到明显提高.仿真证明在信噪比0~100 dB区间内采用本算法为卡尔曼滤波算法的测频误差的1/10左右. 相似文献
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We introduce a system identification method based on weighted-principal component regression (WPCR). This approach aims to identify the dynamics in a linear time-invariant (LTI) model which may represent a resting physiologic system. It tackles the time-domain system identification problem by considering, asymptotically, frequency information inherent in the given data. By including in the model only dominant frequency components of the input signal(s), this method enables construction of candidate models that are specific to the data and facilitates a reduction in parameter estimation error when the signals are colored (as are most physiologic signals). Additionally, this method allows incorporation of preknowledge about the system through a weighting scheme. We present the method in the context of single-input and multi-input single-output systems operating in open-loop and closed-loop. In each scenario, we compare the WPCR method with conventional approaches and approaches that also build data-specific candidate models. Through both simulated and experimental data, we show that the WPCR method enables more accurate identification of the system impulse response function than the other methods when the input signal(s) is colored. 相似文献
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微动目标散射点的微多普勒对目标运动、结构参数的估计具有重要意义。该文针对表面光滑的锥裙目标,首先依据进动锥裙目标的等效散射点模型,推导出散射点的理论微多普勒曲线表达式。结合进动调制的锥裙目标微多普勒曲线为多阶正弦级数叠加的先验信息,提出一种基于参数化时频分析的进动锥裙目标微多普勒曲线提取方法。针对多分量信号组成的锥裙目标回波,该方法利用相干信号单距离多普勒干涉(CSRDI)方法估计锥旋频率,进而利用参数化时频分析估计散射点的微多普勒曲线,之后利用带阻滤波器分离估计得到的散射点回波信号。基于电磁仿真数据验证了所提方法的有效性。 相似文献
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粒子滤波(Particle Filter, PF)是一种有效的参数估计方法。通过对单载波频域均衡(Single Carrier Frequency Domain Equalization, SC-FDE)系统数学模型和粒子滤波原理的分析,将时变信道建模成一阶AR过程,尝试把粒子滤波方法运用到单载波频域均衡系统基于UW的信道估计中去,并给出了算法详细步骤。然后,分别针对三种不同时变程度的信道进行了仿真,并在这三种信道下,分别与LS估计作了误码性能比较。结果表明,在时变条件下,基于粒子滤波的信道估计方法较之线性LS估计能获得良好的误码性能增益,且信道变化越缓慢,这种增益越明显。 相似文献
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临近空间飞行器具有机动特性复杂、运动轨迹多阶段性等特点,在目标跟踪的过程中,易出现由于系统模型误差较大导致跟踪精度降低、滤波发散的问题。针对该问题,在容积卡尔曼滤波的过程中加入衰减因子,通过衰减记忆的方法补偿模型误差;同时,提出了一种实时辨识容积卡尔曼滤波衰减因子的方法,达到自适应跟踪的目的。仿真结果表明:衰减记忆容积卡尔曼滤波算法能够很好地解决模型失配问题,自适应算法实时对衰减因子赋值,避免了衰减因子取值的困难,可以达到更好的跟踪效果。 相似文献
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本文针对一类非线性、多时滞、干扰有界未知的离散系统进行H∞模糊滤波器的设计.首先,利用T-S模糊模型来表达这个非线性、多时滞系统,并将建模误差,通过S-procedure,考虑到滤波器的设计中,建立基于T-S模糊模型的滤波器的存在条件,降低了滤波器设计的保守性.然后根据线性矩阵不等式(LMI)的性质将该模糊滤波器的设计转化为LMI的可行性问题,并采用凸优化技术的内点法求得LMI的可行解,设计出模糊滤波器.仿真结果表明,该方法是有效的. 相似文献
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惯性导航系统(INS)的初始对准误差模型通常为非线性的,对于估计惯导误差普遍采用的是扩展卡尔曼滤波算法(EKF),该方法是在一阶泰勒展开的基础上近似得到的,因而误差较大。粒子滤波算法一种新颖的非线性滤波算法,它较传统的EKF算法具有稳定性好,适用范围广的优点。该文首先介绍了作为粒子滤波理论基础的递推贝叶斯估计的基本概念,说明了重要性函数对于粒子滤波器的设计是至关重要的。随后,给出了一种将不敏卡尔曼滤波(UKF)算法作为重要性函数的UPF算法,并提出将其用于静基座条件下的惯导系统非线性初始对准,通过计算机仿真对比了UPF和EKF的估计效果。仿真结果表明,UPF算法较传统的EKF算法对准时间更快,对准精度更高。 相似文献
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This article puts forward a novel channel estimation and inter-carrier interference (ICI) suppression method for time-varying orthogonal frequency division multiplexing (OFDM) systems. The proposed adaptive finite impulse response (FIR) filter utilizes the time domain correlation of the subcarriers. Based on the one order auto-regressive (AR) model, a modified Kalman filter is exploited to track the channel variance. By solving the Yule-Walker equation, the coefficient of the AR process can be obtained from zero order Bessel function. However, when the channel is assumed not perfectly known, the above criterion will lead to an impractical application. To deal with it, the coefficient of the AR process is taken as a constant. Subsequently a new state space model is deduced and found. Simulation results show that the proposed method can work effectively at the speed of 144 km/h with a phase noise of -85 dBc/Hz at 100 kHz offset. The proposed method yields an improvement bit error rate (BER) compared with three of the existing algorithms with much lower complexity. 相似文献
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根据原始水印构造匹配滤波器,并结合小波估计方法,提出脆弱音频水印的盲检测算法。在假定嵌入水印为噪声的情况下,利用小波不需要原始信号辅助信息即可估计该信号的特点,首先根据给定的估计门限估计了加入水印后的原始信号,从而实现了水印与音频信号分离。然后将水印与估计产生的噪声构成的混合信号送入构造的匹配滤波器作相关运算,根据滤波器的输出响应判断水印及载体是否受到攻击。实验结果表明,所提出方法对噪声、有损压缩、滤波、随机插入与删除等操作具有较高的敏感性。 相似文献