Improved Range Resolution Filters for Rectangular-Pulse Radar Systems

The performance of several new clutter-reduction filters suitable for rectangular-pulse radar systems is investigated. The new filters consist of various approximations and modifications of two filters known to be optimal for certain criteria: the well-known Urkowitz filter which optiizes the clutter improvement ratio, and the newer sidelobe reduction filter which minimizes output noise power subject to peak sidelobe constaints. The new filters are compared usig five basic criteria: clutter improvement ratio, signal-to-noise ratio, sidelobe peak ratio, pulse compression ratio, and filter complexity. The results are summarized in tabular and graphical form.     

椭圆数字滤波器在动态风洞试验中的应用

由于动态风洞试验比常规静态试验有更多的噪声和干扰,传统的数据处理方法不能满足要求,因此综合考虑动态风洞试验数据的特点,比较不同类型数字滤波器的性能,选择运用椭圆数字滤波器,对动态风洞试验数据进行处理。给出了设计椭圆数字滤波器时所需要的近似求解雅可比椭圆函数的方法,并简单介绍了椭圆数字滤波器的设计过程,给出了必要的设计公式。根据某项目动态风洞试验的试验数据设计了一款低通椭圆数字滤波器,有效地减少了信号中的噪声和干扰,并已成功地用于项目中。     

Performance Bounds for Continuous-time Filters in the Presence of Modeling Errors

We are concerned with obtaining bounds on the performance of Kalman-type, linear, continuous-time filters susceptible to modeling errors. Limiting the discussion to stationary performance, we obtain bounds on the performance index, the mean square error of estimates for suboptimal and optimal (Kalman) filters. The bounds are expressed in terms of the model matrices and the range of errors of the matrices. The results are useful to a designer in comparing the performance of a suboptimal filter with that of the optimal filter when he has information on the range of modeling errors. The tightness of the bounds is shown by an application of the results in the estimation of the motion of an aircraft carrier at sea.     

Interrelationship of single-filter and multiple-model adaptivealgorithms

An equivalent filter bank structure for multiple model adaptive estimation (MMAE) is developed that uses the residual and state estimates from a single Kalman filter and linear transforms to produce equivalent residuals of a complete Kalman filter bank. The linear transforms, which are a function of the differences between the system models used by the various Kalman filters, are developed for modeling differences in the system input matrix, the output matrix, and the state transition matrix. The computational cost of this new structure is compared with the cost of the standard Kalman filter bank (SKFB) for each of these modeling differences. This structure is quite similar to the generalized likelihood ratio (GLR) structure, where the linear transforms can be used to compute the matched filters used in the GLR approach. This approach produces the best matched filters in the sense that they truly represent the time history of the residuals caused by a physically motivated failure model     

Poly-phase codes and optimal filters for multiple user ranging

A technique is introduced to select poly-phase codes and optimal filters of a pulse compression system that have specific temporal and frequency characteristics. In the particular problem under study, multiple vehicles are assigned unique codes and receiver filters that have nearly orthogonal signatures. Narrowband users, that act as interference, are also present within the system. A code selection algorithm is used to select codes which have low autocorrelation sidelobes and low cross correlation peaks. Optimal mismatched filters are designed for these codes which minimize the peak values in the autocorrelation and the cross correlation functions. An adjustment to the filter design technique produces filters with nulls in their frequency response, in addition to having low correlation peaks. The method produces good codes and filters for a four-user system with length 34 four-phase codes. There is considerable improvement in cross and autocorrelation sidelobe levels over the matched filter case with only a slight decrease in the signal-to-noise ratio (SNR) of the system. The mismatched filter design also allows the design of frequency nulls at any frequency with arbitrary null attenuation, null width, and sidelobe level, at the cost of a slight decrease in processing gain     

Effects of output filter on cross regulation in SRC

Cross regulation performance of multioutput series resonant converter (SRC) topologies using capacitive or inductive filters is analyzed. The steady state cross regulation characteristics are derived using the state-plane techniques and are illustrated by the examples of two-output SRCs with capacitive and inductive filters. The characteristic curves show that over some range of output currents, the cross regulation performance of an SRC with an inductive filter is much improved over the SRC with capacitance filter and less dependent on the tolerances in leakage inductances and the loading on unregulated outputs. It is shown that the converter control characteristics of an SRC with an inductive filter are relatively unaffected by the addition of the second output. The theoretical results are verified by simulation     

Third world radiation threats to satellites

The era of hardening military satellites against nuclear events, lasers, and high-power microwaves, appears to have come to an end. A case is made here for maintaining rudimentary nuclear, laser, and high-power microwave (HPM) hardening requirements in order to protect against developing third world threats. The third world nuclear threat is well known. Less appreciated is the fact that third world laser and microwave threats have changed radically in the past few years     

A wavelet multiresolution analysis for spatio-temporal signals

The wavelet filters of the conventional 3D multiresolution analysis possess homogeneous spatial and temporal frequency characteristics which limits one's ability to match filter frequency characteristics to signal frequency behavior. Also, the conventional 3D multiresolution analysis employs an oct-tree decomposition structure which restricts the analysis of signal details to identical resolutions in space and time. This paper presents a 3D wavelet multiresolution analysis constructed from nonhomogeneous spatial and temporal filters, and an orthogonal sub-band coding scheme that decouples the spatial and temporal decomposition processes     

一种基于Gabor滤波的不同聚焦图像融合方法

提出了一种基于Gabor滤波对不同聚焦图像融合的方法。通过取不同方向的Gabor滤波器对待融合的图像进行多方向滤波,从而提取出不同方向的高频能量,再通过比较高频能量大小来判断属于清晰还是模糊像素,以此达到融合不同聚焦图像的目的。实验表明这种方法简单有效,给出了图像融合的实验结果,并与小波变换和简单取平均融合结果进行了比较。     

自适应滤波技术的研究

应用常规卡尔曼滤波器(KF)要求知道系统精确的数学模型和系统噪声与量测噪声的统计特性,才能获得理想的滤波效果,否则可能产生发散现象。人们越来越倾向于利用自适应滤波(AKF)技术来解决发散的问题。针对AKF技术的研究现状,本文探讨一种结构简单、实时性较强、工程上比较实用的AKF算法。仿真结果表明,这种算法具有较强的自适应性,为一种实用而有效的滤波方法。     

Real-Time Tracking Filter Evaluation and Selection for Tactical Applications

Five important tracking filters that are often candidates for implementation in systems that must track maneuvering vehicles are compared in terms of tracking accuracy and computer requirements for tactical applications. A rationale for selecting among these filters, which include a Kalman filter, a simplified Kalman filter, an ?-? filter, a Wiener filter, and a two-point extrapolator, is illustrated by two examples taken from the authors' recent experience.     

采用一组卡尔曼滤波器检测发动机传感器故障

在发动机全功能数字电子控制系统中,提高传感器工作的可靠性是十分重要的,除了不断对传感器本身的性能加以改进提高外,现在广泛地采用了余度技术。近二十年来对解析余度(Analyt ical Redundancy)进行了广泛的研究,解析余度(AR)方法是基于各状态变量之间存在的解析关系,在系统可观条件下,利用无故障的输出测量值去估计(构造)已故障传感器正常工作状态时的输出信息,从而实现对故障的检测、隔离与重构,保证控制系统具有预定的控制性能。      

The Susceptivity of MTI Systems to White Noise

The performance of various coherent MTI systems in the presence of white noise is investigated. The single-pulse signal-to-noise ratios at the output of the filters are presented for the case of large system bandwidth. Generalized results, calculated as a function of the system's bandwidth, are given. Finally, those results are compared to the optimum signal-to-noise acheivable by a matched filter.     

GPS多径信号的自适应滤波估计方法

 研究全球定位系统(GPS)多径信号估计的问题。通过分析自适应滤波器的原理,建立了数字中频信号处理的数学模型,提出一种用自适应滤波实现GPS多径幅度、码相位和载波相位估计的方法。该方法采用不同延迟的伪随机序列对信号进行解扩、解调和累加,得到了作为期望信号的系列自适应滤波相关值。对该方法与其他3种方法进行了理论上的分析比较,得出本方法具有信噪比高、自适应滤波性能好、带有码相位信息和不存在载波模糊度问题等优点。根据各种滤波器算法的特点和本应用的需求,给出了选用递归最小二乘算法实现的方法。通过计算机仿真,验证了提出的方法能够在14 dB的信噪比下,以1个采样间隔的时间延迟分辨率和0.005周的载波相位估计精度估计出GPS L1的多径信号。     

On a decoupled multitarget tracking algorithm

An analysis is conducted of the optimality of a decoupled tracking filtering algorithm for addressing the problem of tracking multiple targets with correlated measurements and maneuvers. It is proved that the decoupled filters are, in general, suboptimal and are not in fact Kalman filters. However, it is shown also that if the standard Kalman filter is asymptotically stable, the decoupled filters will converge asymptotically to the stable version of the standard Kalman filter. For the case of time-invariant measurement and process noise covariance, a simple sufficient condition guaranteeing the asymptotical stability of the decoupled filters are given     

Square root parallel Kalman filtering using reduced-order localfilters

The basic parallel Kalman filtering algorithms derived by H.R. Hashemipour et al. (IEEE Trans. Autom. Control. vol.33, p.88-94, 1988) are summarized and generalized to the case of reduced-order local filters. Measurement-update and time-update equations are provided for four implementations: the conventional covariance filter, the conventional information filter, the square-foot covariance filter, and the square-foot information filter. A special feature of the suggested architecture is the ability to accommodate parallel local filters that have a smaller state dimension than the global filter. The estimates and covariance or information matrices (or their square roots) from these reduced-order filters are collated at a central filter at each step to generate the full-size, globally optimal estimates and their associated error covariance or information matrices (or their square roots). Aspects of computational complexity and the ensuing tradeoff with communication are discussed     

Self-oscillating DC-to-DC switching converters with transformer characteristics

Fourth-order converters with both input and output filters are analyzed in self-oscillating sliding mode. The boost converter with output filter and the Cuk converter are shown to have stable dynamics and an equilibrium point with transformer characteristics. The analytical predictions are verified by experimental results.     

Kalman filtering for matrix estimation

A general discrete-time Kalman filter (KF) for state matrix estimation using matrix measurements is presented. The new algorithm evaluates the state matrix estimate and the estimation error covariance matrix in terms of the original system matrices. The proposed algorithm naturally fits systems which are most conveniently described by matrix process and measurement equations. Its formulation uses a compact notation for aiding both intuition and mathematical manipulation. It is a straightforward extension of the classical KF, and includes as special cases other matrix filters that were developed in the past. Beyond the analytical value of the matrix filter, it is shown through various examples arising in engineering problems that this filter can be computationally more efficient than its vectorized version.     

Turboshaft engine air particle separation

This contribution addresses air particle separation technologies (EAPS) used for helicopter turboshaft engines that operate around unprepared airfields. Three key technologies are discussed. These are: vortex tube separators, inertial particle separators and inlet barrier filters. Some of these technologies are retrofitted or designed around specified airframes; other ones are an integral part of the turboshaft inlet design. For the vortex tubes, a complete review of the current intellectual property is reviewed, and a first-order theoretical model is presented to corroborate the performance of this technology. The inertial particle separators are designed as part of the engine inlets. This technology is more amenable to computational fluid dynamic modelling, coupled with particle dynamics and rebound effects. The inlet barrier filters are part of a large category of filtration systems. A first-order filter theory is derived to predict filter performance as a function of key parameters and useful operation time. The integration of the various EAPS with the helicopter system are discussed.     

Federated square root filter for decentralized parallel processors

An efficient, federated Kalman filter is developed for use in distributed multisensor systems. The design accommodates sensor-dedicated local filters, some of which use data from a common reference subsystem. The local filters run in parallel, and provide sensor data compression via prefiltering. The master filter runs at a selectable reduced rate, fusing local filter outputs via efficient square root algorithms. Common local process noise correlations are handled by use of a conservative matrix upper bound. The federated filter yields estimates that are globally optimal or conservatively suboptimal, depending upon the master filter processing rate. This design achieves a major improvement in throughput (speed), is well suited to real-time system implementation, and enhances fault detection, isolation, and recovery capability