Interacting multiple model fixed-lag smoothing algorithm forMarkovian switching systems

We investigate a suboptimal approach to the fixed-lag smoothing problem for Markovian switching systems. A fixed-lag smoothing algorithm is developed by applying the basic Interacting Multiple Model (IMM) approach to a state-augmented system. The computational load is roughly d (the fixed lag) times beyond that of filtering for the original system. In addition, an algorithm that approximates the “fixed-lag” mode probabilities given measurements up to current time is proposed. The algorithm is illustrated via a target tracking simulation example where a significant improvement over the filtering algorithm is achieved at the cost of a time delay (i.e., data up to time k are used to produce the smoothed state estimate at time k-d where the fixed large d>0). the IMM fixed-lag smoothing performance for the given example is comparable to that of an existing IMM fixed-interval smoother. Compared with fixed-interval smoothers, the fixed-lag smoothers can be implemented in real-time with a small delay     

基于数字滤波的低频时码秒脉冲抖动平滑方法研究

低频时码授时信号在接收时,由于环境等因素的影响会导致解调得到的低频时码秒脉冲出现抖动。为减小该抖动现象对低频时码定时精度的影响,基于我国低频时码授时系统(BPC),研究并设计基于数字滤波的秒脉冲抖动平滑方法,通过仿真实验,验证分析了最小均方误差(LMS)自适应滤波算法和卡尔曼滤波算法的有效性和抖动平滑性能。结果表明,低频时码秒脉冲的抖动现象可以通过BPC 1PPS (one pulse per second)和本地1PPS之间的相位差波动情况反映;LMS自适应滤波算法和卡尔曼滤波算法对BPC 1PPS的抖动平滑处理均有明显效果,卡尔曼滤波算法的抖动平滑效果更优,但存在一定的收敛时间,LMS自适应滤波算法的滤波结果响应速度快,但抖动平滑性能受滤波器阶数的影响。所以,在实际应用中,应根据实际需求选择合适的滤波器及相关参数。     

基于固定区间最优平滑的传递对准精度评估

惯导系统传递对准是战术导弹发射前必须完成的任务,其对准精度直接影响导弹系统的制导精度。为评估传递对准精度性能,在介绍传递对准精度评估原理的基础上,研究了Kalman固定区间最优平滑算法;并从理论上分析了顺序滤波与逆序平滑的关系,得出平滑依赖于滤波的结论。通过实测数据半物理仿真试验证明了理论分析的正确性,表明固定区间最优平滑算法能有效地评估传递对准精度,并与间接法对比得出间接法与最优平滑算法具有一致性。     

Fixed-interval retrodiction approach to Bayesian IMM-MHT formaneuvering multiple targets

In a Bayesian framework, we propose a hierarchy of suboptimal retrodiction algorithms that generalize Rauch-Tung-Striebel (RTS) fixed-interval smoothing to multiple hypothesis tracking (MHT) applications employing interacting multiple model (IMM) methods (IMM-MHT). As a limiting case we obtain new simple formulae for suboptimal fixed-interval smoothing applied to Markovian switching systems. Retrodiction techniques provide uniquely interpretable and accurate trajectories from ambiguous MHT output if a certain (small) time delay is tolerated. By a simulated example with two maneuvering targets that operate closely spaced under relatively hard conditions we demonstrate the potential gain by fixed-interval retrodiction and provide a quantitative idea of the achievable track accuracy and mean time delay involved     

R-T-S平滑算法与抗差Kalman在数据后处理中的应用

为了提高组合导航系统后处理精度和数据稳定性,将R-T-S最优固定区间平滑算法引入数据后处理中,在前向Kalman滤波的基础上,进行了后向R-T-S最优固定区间平滑处理,并针对GPS观测值中存在异常的问题,将抗差Kalman滤波算法引入数据后处理中,并对该算法进行实物仿真。结果表明,与传统Kalman滤波相比,R-T-S平滑算法不仅可以提高位置、姿态精度,而且在卫星信号失锁的情况下精度也得到显著改善,并且在不丢星的时刻,抗差Kalman滤波可以有效处理GPS信号中的异常观测值,遏制滤波发散,是一种有效的数据处理方法。     

ADAPTIVE MULTIPLE MODEL FILTER USING IMM AND STF

Consider a discrete- time stochastic hybridsystem　 x( k 1 ) =f( k, ( k) ,x( k) ,m( k 1 ) ) ζ( k,m( k 1 ) ) q( k) ( 1 )　 z( k 1 ) =h( k 1 ,x( k 1 ) ,m( k 1 ) ) v( k 1 ,m( k 1 ) ) ( 2 )where state x∈ Rn;measurement z∈ Rm;input∈ Rp;modeling noise q( k)∈ Rqis a zero- mean,Gaussian white noise with covariance Q( k) ;measurement noise v( k 1 )∈ Rm is also a zero-mean,Gaussian white noise with covariance R( k 1 ) ;q( k) and v( k) are statistically indepen-dent. Th…     

晃动环境下组合导航系统精度事后评估算法研究

海风、波浪、海流等因素会产生舰船的摇摆晃动,从而给舰船导航系统精度带来严重干扰.固定区间平滑滤波处理算法能够利用观测时间间隔内全部观测信息得到状态的最小方差估计,对导航精度进行事后评估.在研究晃动环境下的SINS/GP S组合导航应用平滑滤波算法的相关原理的基础上,首先利用Kalman滤波器进行组合导航,存储相关信息后按时间逆序利用固定区间平滑滤波算法进行事后分析.该方法可以针对不同的海况以及不同的海上作业需求,有效地为组合导航系统精度提供检验标准,考核各种海洋环境下的导航系统精度.     

基于多特征的支持向量机印鉴识别

印鉴真伪鉴别的难点要求识别系统同时具备同类印鉴的鲁棒性及异类印鉴的敏感性.针对这一难点,本文提出了一种基于多特征的支持向量机(Support Vector Machine,SVM)鉴别算法,根据多类特征以及支持向量机的自适应寻优特性,获得对真伪印鉴的鉴别.采用Gabor滤波器获得频率特征,采用差图像获得结构特征,采用原图像和极坐标图像的奇异值获得不变量特征.采用支持向量机(Support Vector Machine,SVM)对印鉴进行真伪鉴别.实验表明,本文方法具有很高的真伪鉴别能力.     

一种基于盲同态解卷积的SAR成像自聚焦算法

针对大气扰动及飞行平台不稳引起机载合成孔径雷达(SAR)图像散焦的问题,提出了一种新的自聚焦算法来估算运动误差。该算法是基于运动误差函数及场景散射函数平滑特性的差异来进行估计的,利用复对数变换将图像的幅度与相位信息分离,进而分别对相位及幅度信息进行处理。运动误差通常为慢变函数,而场景的散射信息具有某种随机特性。因此,经过复对数变换后,运动误差及散射信息可以通过滤波器进行分离,将相位中的随机噪声去除,从而保留了慢变的运动误差函数。为了去除噪声信息,需要建立一个平滑滤波器,利用Daubechies小波的尺度函数构造Riesz基向量,从而建立了正交子空间,通过所建立信号子空间及噪声子空间组建平滑滤波器,最终可以获得准确的运动误差。在实验部分,分别利用仿真数据及实测数据对本文方法进行验证,最终结果分析表明该方法具有很高的估计精度及执行效率。     

A robust Poisson multi-Bernoulli filter for multi-target tracking based on arithmetic average fusion

The coalescence and missed detection are two key challenges in Multi-Target Tracking (MTT). To balance the tracking accuracy and real-time performance, the existing Random Finite Set (RFS) based filters are generally difficult to handle the above problems simultaneously, such as the Track-Oriented marginal Multi-Bernoulli/Poisson (TOMB/P) and Measurement-Oriented marginal Multi-Bernoulli/Poisson (MOMB/P) filters. Based on the Arithmetic Average (AA) fusion rule, this paper proposes a novel fusion framework for the Poisson Multi-Bernoulli (PMB) filter, which integrates both the advantages of the TOMB/P filter in dealing with missed detection and the advantages of the MOMB/P filter in dealing with coalescence. In order to fuse the different PMB distributions, the Bernoulli components in different Multi-Bernoulli (MB) distributions are associated with each other by Kullback-Leibler Divergence (KLD) minimization. Moreover, an adaptive AA fusion rule is designed on the basis of the exponential fusion weights, which utilizes the TOMB/P and MOMB/P updates to solve these difficulties in MTT. Finally, by comparing with the TOMB/P and MOMB/P filters, the performance of the proposed filter in terms of accuracy and efficiency is demonstrated in three challenging scenarios.     

Robust Flight Control Design for the HIRM based on Linear Quadratic Control

In this paper the application of Linear Quadratic Optimal Control based techniques to the HIRM (High Incidence Research Model) Robust Flight Control design problem is considered. The structure of the proposed controller is basically a Proportional Integral action, both for the longitudinal and for the lateral-directional parts, designed with optimality criteria in order to achieve the performance and robustness requirements. Moreover, the control scheme is completed by the compensation of some physical non linearities, some demand shaping filters and a switching logic based on the angle of attack and on the Mach number. Most of the design requirements are easily satisfied; some others need a heavier tuning of the controller design parameters. A procedure to tune such parameters, formulated in terms of an optimization problem, is proposed. Simulation results, from the HIRM automated evaluation procedure are also provided at the end of the paper, from which it is shown that the proposed controller meets the requirements.     

Performance enhancement of a multiple model adaptive estimator

We describe performance improvement techniques for a multiple model adaptive estimator (MMAE) used to detect and identify control surface and sensor failures on an unmanned flight vehicle. Initially failure identification was accomplished within 4 s of onset, but by removing the “β dominance” effects, bounding the hypothesis conditional probabilities, retuning the Kalman filters, increasing the penalty for measurement residuals, decreasing the probability smoothing, and increasing residual propagation, the identification time was reduced to 2 s     

Multiple-model estimation with variable structure- part VI: expected-mode augmentation

A new class of variable-structure (VS) algorithms for multiple-model (MM) estimation is presented, referred to as expected-mode augmentation (EMA). In the EMA approach, the original set of models is augmented by a variable set of models intended to match the expected value of the unknown true mode. These models are generated adaptively in real time as (globally or locally) probabilistically weighted sums of mode estimates over the model set. This makes it possible to cover a large continuous mode space by a relatively small number of models at a given accuracy level. The paper presents new theoretical results for model-set design, a general formulation of the EMA approach, along with theoretical analysis and justification, and three algorithms for its practical implementation. The performance of the proposed EMA algorithms is evaluated via simulation of a generic maneuvering target tracking problem.     

Decorrelation of broadband signals by Toeplitz-Block-Toeplitzstructuring

We propose F-norm of the cross-correlation part of the array covariance matrix as a measure of correlation between the impinging signals and study the performance of different decorrelation methods in the broadband case using this measure. We first show that dimensionality of the composite signal subspace, defined as the number of significant eigenvectors of the source sample covariance matrix, collapses in the presence of multipath and the spatial smoothing recovers this dimensionality. Using an upper bound on the proposed measure, we then study the decorrelation of the broadband signals with spatial smoothing and the effect of spacing and directions of the sources on the rate of decorrelation with progressive smoothing. Next, we introduce a weighted smoothing method based on Toeplitz-block-Toeplitz (TBT) structuring of the data covariance matrix which decorrelates the signals much faster than the spatial smoothing. Computer simulations are included to demonstrate the performance of the two methods     

基于变结构多模型的SINS/DVL组合导航算法

对于无人水下航行器来说,SINS/DVL组合导航是其主要导航方式,由于DVL自身作用距离的限制,虽然它可以在水跟踪模式下工作,但洋流速度作为其测量误差会导致SINS/DVL组合导航性能下降甚至失败.针对上述问题,基于有向图切换方法,设置洋流速度模型群,利用所设置的模型群切换策略对子模型群进行激活和终止,通过变结构多模型...     

An LMS Adaptive Array for Multipath Fading Reduction

Multipath fading often poses a serious hindrance in radiocommunication. The application of a least-mean-square (LMS)adaptive array to the problem of multipath fading reduction is discussed. However, it is known that multipath components are in general correlated with one another. We examine the effect of the correlation on the performance of the LMS adaptive array. When the correlation coefficient does not equal or approximate 1, the LMS adaptive array suppresses the multipath signals significantly by nulling. On the other hand, when the correlation coefficient nearly equals 1, the LMS adaptive array prevents the output signalpower from decreasing. Therefore, the LMS adaptive array mayreduce the multipath fading effectively for any correlation coefficient value. A reference signal in the LMS adaptive array is also discussed. It is shown that synchronization in the referencesignal generation must be extremely accurate. Moreover, aprocessor configuration is proposed which may generate thereference signal with the required accuracy.     

Reliable flight performance assessment of multirotor based on interacting multiple model particle filter and health degree

Multirotor has been applied to many military and civilian mission scenarios. From the perspective of reliability, it is difficult to ensure that multirotors do not generate hardware and software failures or performance anomalies during the flight process. These failures and anomalies may result in mission interruptions, crashes, and even threats to the lives and property of human beings. Thus, the study of flight reliability problems of multirotors is conductive to the development of the drone industry and has theoretical significance and engineering value. This paper proposes a reliable flight performance assessment method of multirotors based on an Interacting Multiple Model Particle Filter (IMMPF) algorithm and health degree as the performance indicator. First, the multirotor is modeled by the Stochastic Hybrid System (SHS) model, and the problem of reliable flight performance assessment is formulated. In order to solve the problem, the IMMPF algorithm is presented to estimate the real-time probability distribution of hybrid state of the established SHS-based multirotor model, since it can decrease estimation errors compared with the standard interacting multiple model algorithm based on extended Kalman filter. Then, the reliable flight performance is assessed with health degree based on the estimation result. Finally, a case study of a multirotor suffering from sensor anomalies is presented to validate the effectiveness of the proposed method.     

一种变步长LMS自适应滤波算法研究

为了解决最小均方(LMS)算法的稳定性以及收敛速度和稳态误差之间的矛盾,提出了一种复数型自适应变步长的LMS算法,它的权系数的调整取决于误差曲面在新权值点上的梯度。分析了新算法的收敛特性以及参数选择对算法性能的影响。算法具有较快的收敛速度、鲁棒稳定性且运算小易于实现的特点。计算机仿真的结果与理论分析相一致,证实了算法的收敛性能优于标准的LMS算法并且具有较好的实用性。     

An efficient active ripple filter for use in DC-DC conversion

When low ripple is required from a switched mode dc-dc converter, dissipative active filters offer an alternative to passive LC and coupled inductor filters. Analytical and experimental results are presented for a simple active ripple filter. The filter employs a pair of current transformers as sensors for feedforward and feedback control and two metal-oxide-semiconductor field-effect transistors (MOSFETs) as cancellation current drivers. Measurements demonstrate good ripple attenuation up to 5 MHz, more than 70 dB being obtained at 100 kHz, the switching frequency of a test converter. The overall efficiency was measured as 95%, with room for further improvement. The filter is suitable for input and output smoothing in dc-dc converters for aerospace and other critical applications     

Spectral Analysis of Optimal and Suboptimal Gyro Monitoring Filters

Gyro monitoring filters are used to estimate and correct gyro drift rates of local-level inertial navigation systems. Conventional gyro monitoring filters are usually designed based on a simplified model of gyro drift rate. Furthermore, the effectiveness of these filters-and of many filters of the "Kalman" type-is often measured in terms of the root mean square (rms) criterion in contrast to the spectral content criterion typical of classical Wiener filtering theory. This paper has two objectives: to propose a gyro monitoring filter which is based on a more detailed model of gyro drift rate; and to propose a method of filter performance evaluation which uses as criterion a measure of the spectral content of the error process. The proposed gyro monitoring filter is shown to have improved spectral contents resulting in superior navigation performance for the gyro error models used in the calculations (comparable to commercial-grade aircraft gyros).