The effects of IF bandpass mismatch errors on adaptive cancellation

The effects of IF bandpass mismatch errors on adaptive cancellers are investigated. Frequency mismatch errors occur because of errors in the synthesis process of the bandpass filters which are designed to be identical and are in each input channel. Tapped-delay line transversal filters can be used to compensate for these frequency mismatches and thus improve cancellation performance. A pole/zero error model of the filters is developed whereby closed-form solutions of the maximum achievable average cancellation are obtained. This cancellation is a function of the order of the ideally matched frequency filters, the number of time-delay taps in the compensating transversal filter, the bandwidth-tapped time-delay product, and the constraints on these parameters. A design procedure is outlined for optimizing the canceller with respect to these parameters and their constraints; specifically, results are presented for Butterworth-type input filters. It is shown that an arbitrarily low output noise residue cannot be achieved by arbitrarily increasing the number of time-delay taps     

A sampling-based approach to wideband interference cancellation

Classical adaptive array schemes which use only complex spatial weights are inherently narrowband and consequently perform poorly when attempting to suppress wideband interference. The common solution to this problem is the use of tapped delay line filters in each spatial channel to facilitate space-time adaptive processing (STAP). The higher performance provided by the STAP architecture comes at the cost of a considerable increase in complexity. This paper presents a simpler technique based on programmable time adjustable sampling (TAS) that provides a limited number of wideband degrees of freedom. Two TAS methods are introduced: TAS-sidelobe canceler (TAS-SLC) is based on the sidelobe canceler, while TAS-minimum variance beamformer (TAS-MVB) is derived from the minimum variance beamformer. TAS is implemented by adjusting the sampling instant at selected array channels. TAS-SLC consists of controlling the sampling in the main channel of the sidelobe canceler With TAS-MVB array complex weights are substituted with TAS time delays. The performance of TAS methods with wideband interference is compared to the conventional sidelobe canceler and minimum variance beamformers. It is shown that TAS-SLC provides better performance than the sidelobe canceler, while TAS-MVB outperforms the minimum variance beamformer     

Application of Gram-Schmidt algorithm to fully adaptive arrays

The Gram-Schmidt orthogonalization (GSO) algorithm has excellent numerical performance and is readily applicable to systolic implementations such as in a field of adaptive cancellation systems. A modified GSO algorithm for a fully adaptive array is proposed and computer simulations show that the proposed algorithm gives superior performance. A systolic implementation of the proposed GSO algorithm for fully adaptive array is presented. A feedback mode GSO algorithm for use with analog weights is also presented and has been shown to have excellent performance in the presence of weight errors     

Design and Evaluation of an Adaptive MTI Filter

The design and evaluation of an adaptive moving target indicator (MTI) filter, the adaptive canceler for extended clutter (ACEC) is dealt with, taking into consideration adaptivity to clutter mean Doppler frequency. This consideration is one of the most important operational requirements in adaptive MTI's and permits a relatively simple hardware implementation as compared to more general optimization and adaptivity criteria (briefly described). The ACEC's algorithm compensates in real time for the clutter mean Doppler frequency. Performances have been obtained by digital computer simulation in various operational conditions.     

Clutter Covariance Matrix Form Effect on Adaptive MTI Performance

The performance of an adaptive moving target indicator (MTI), which employs a Wiener predictor by means of a transversal filter, is discussed, taking into consideration the effect of the form of the clutter covariance matrix on the MTI performance. It is emphasized that the main tap position in the transversal filter is an important factor which provides degrees of freedom in the clutter covariance matrix to improve the MTI performance. Calculation results show that by exploiting these degrees of freedom, excellent performance is feasible, in particular shorter transient response.     

Adaptive canceler and pulse compressor interactions

Performance results for the sidelobe level of a compressed pulse that has been preprocessed through an adaptive canceler are obtained. The adaptive canceler is implemented using the sampled matrix inversion algorithm. Because of finite sampling, the quiescent compressed pulse sidelobe levels are degraded due to the preprocessing of the main channel input data stream (the uncompressed pulse) through an adaptive canceler. It is shown that if N is the number of input canceler channels (main and auxiliaries) and K is the number of independent samples per channel, then K/N can be significantly greater than one in order to retain sidelobes that are close to the original quiescent sidelobe level (with no adaptive canceler). Also it is shown that the maximum level of degradation is independent of whether pulse compression occurs before or after the adaptive canceler if the uncompressed pulse is completely contained within the K samples that are used to calculate the canceler weights. This same analysis can be used to predict the canceler noise power level that is induced by having the desired signal present in the canceler weight calculation     

Reiterative median cascaded canceler for robust adaptive array processing

A new robust adaptive processor based on reiterative application of the median cascaded canceler (MCC) is presented and called the reiterative median cascaded canceler (RMCC). It is shown that the RMCC processor is a robust replacement for the sample matrix inversion (SMI) adaptive processor and for its equivalent implementations. The MCC, though a robust adaptive processor, has a convergence rate that is dependent on the rank of the input interference-plus-noise covariance matrix for a given number of adaptive degrees of freedom (DOF), N. In contrast, the RMCC, using identical training data as the MCC, exhibits the highly desirable combination of: 1) convergence-robustness to outliers/targets in adaptive weight training data, like the MCC, and 2) fast convergence performance that is independent of the input interference-plus-noise covariance matrix, unlike the MCC. For a number of representative examples, the RMCC is shown to converge using ~ 2.8N samples for any interference rank value as compared with ~ 2N samples for the SMI algorithm. However, the SMI algorithm requires considerably more samples to converge in the presence of outliers/targets, whereas the RMCC does not. Both simulated data as well as measured airborne radar data from the multichannel airborne radar measurements (MCARM) space-time adaptive processing (STAP) database are used to illustrate performance improvements over SMI methods.     

An MTI Technique for Processing Radar Measurements of a Waking Reentry Body

A processing technique based on pulse-cancellation techniques familiar in moving target indicator (MTI) radar is proposed for separating (in Doppler) echoes of a reentry body traveling at hypersonic velocities from those of its lower velocity turbulent wake appearing in the same range cell. The cancellation technique is implemented by forming the sum of the products of binomial weighting coefficients of alternating sign with the complex echoes of a small number of closely spaced transmitted coherent pulses; thereby, in effect, synthesizing a digital canceler. The ability of the two-and three-pulse canceler to estimate body RCS in the presence of attached wake is demonstrated by employing coherent burst data collected by the AMRAD radar for a mission flown at the White Sands Missile Range. Estimates of body RCS obtained from the two-and three-pulse canceler compare favorably to the corresponding estimates obtained from a 30-pulse Doppler periodogram for this mission. Expressions for both the achievable wake rejection ratio and the mean and standard deviation of the body power estimate of the N-pulse canceler are derived as a function of the wake parameters, assuming Gaussian wake statistics.     

Multipath-adaptive GPS/INS receiver

Multipath interference is one of the contributing sources of errors in precise global positioning system (GPS) position determination. This paper identifies key parameters of a multipath signal, focusing on estimating them accurately in order to mitigate multipath effects. Multiple model adaptive estimation (MMAE) techniques are applied to an inertial navigation system (INS)-coupled GPS receiver, based on a federated (distributed) Kalman filter design, to estimate the desired multipath parameters. The system configuration is one in which a GPS receiver and an INS are integrated together at the level of the in-phase and quadrature phase (I and Q) signals, rather than at the level of pseudo-range signals or navigation solutions. The system model of the MMAE is presented and the elemental Kalman filter design is examined. Different parameter search spaces are examined for accurate multipath parameter identification. The resulting GPS/INS receiver designs are validated through computer simulation of a user receiving signals from GPS satellites with multipath signal interference present The designed adaptive receiver provides pseudo-range estimates that are corrected for the effects of multipath interference, resulting in an integrated system that performs well with or without multipath interference present.     

一种机载雷达两级降维空时二维自适应处理方法

 提出了一种机载相控阵雷达杂波抑制的两级降维空时自适应处理(STAP)方法,即：先根据杂波分布先验信息进行空时局域化(JDL)降维处理,然后对局域化输出进行多级维纳滤波(MWF),实现二次降维。该方法综合了固定结构和自适应结构降维技术的优点,将JDL处理引入到MWF中,从而有效降低MWF的杂波自由度。计算机仿真和理论分析表明本文方法比JDL自适应处理方法和全空时MWF方法具有更小的运算量,对阵元随机幅相误差具有很好的容差能力,是一种稳健的两级降维自适应处理方法。最后,基于仿真和实测数据的实验验证了算法的有效性。     

An Adaptive MTI for Weather Clutter Suppression

A digital realization of an adaptive clutter-locking loop is presented. The purpose of the loop is to estimate the mean Doppler frequency of the clutter. The clutter spectrum is then shifted toward the zero Doppler by this estimate. A fixed moving target indicator (MTI) canceler following the loop suppresses the shifted clutter. Experimental simulations illustrate the feasibility of the loop. Results indicate that the proposed canceler works significantly better than a fixed canceler, while not as well as the 10-pulse moving target detector (MTD) processor. However, the complexity of the MTD is significantly more than the relatively simple adaptive processor presented here.     

Time jitter analysis for quadrature sampling

Time jitter in the quadrature sampling processes is modeled and the performance of an adaptive cancellation system in the presence of such time jitter is analyzed. It is shown that the decorrelation due to time jitter depends on the magnitude of the jitter, the sampling scheme used, the bandwidth of the signal and the intermediate frequency (IF) preceding the analog-to-digital (A/D) conversion stages. The performance of a sidelobe cancellation system in the presence of time jitter, for several sampling approaches, is evaluated numerically as well as simulated. The results show that the direct quadrature sampling scheme with a lower IF provides superior performance for an adaptive cancellation system     

Multicomponent receiver architectures for GPS interference suppression

The global positioning system (GPS) is a one-way satellite-based navigation system employing spread-spectrum techniques that is widely used for commercial and military applications. Although the very low signal-to-noise ratio (SNR) is handled by the large spreading gain, GPS is susceptible to high-power interference signals and various types of jammers. We propose multicomponent receiver architectures for GPS interference suppression. A conventional antenna system is first considered which utilizes a minimum-variance distortionless-response (MVDR) beam former and assumes that the GPS signal angle of arrival (AOA) and the antenna model are known at the receiver. However, this receiver is sensitive to AOA estimation errors and can have a high computational complexity. This sensitivity problem is eliminated by a multicomponent system based on a multistage matched filter (MF). Since this MF receiver also has a high computational complexity because the jammer AOAs must be estimated, we introduce a blind interference canceler based on the constant modulus (CM) array that is insensitive to AOA estimation errors and has a low computational complexity. Computer simulations are provided to illustrate the performance of the various systems for interference suppression in example signal scenarios.     

自适应增量粒子滤波方法

提出自适应增量粒子滤波(AIPF)的概念和定义,建立AIPF模型,给出了分析方法和主要的计算步骤.对于许多实际工程(如深空探测)中存在的由未知系统误差的影响而无法精确建立量测似然函数及滤波过程中的粒子匮乏等问题,通过增量粒子滤波模型对滤波过程中的粒子数进行自适应调整,从而消除这种未知系统和滤波粒子匮乏的影响,自动调整粒子,提高非线性滤波的精度.仿真计算中,滤波误差均值和方差分别降低为原来的3.8%和19.6%.该方法有效地改善了滤波效果,计算简单,便于工程应用.      

Detection Performance of Soft-Limited Phase-Coded Signals

General analytic expressions are developed for the soft-limited digital pulse compressor (matched filter). This theoretical development is then used for the hardware realization of a two-channel (I,Q), 3-bit-limited digital pulse compressor with a compression ratio of 255: 1. The realized hardware uses state of the art integrated circuit devices. An experimental laboratory setup is described. This setup is used to study hard-limited versus 3-bit-limited matched-filter performance characteristics with the data in the following areas: 1) constant false alarm rate (CFAR) characteristics as a function of threshold settings and noise levels; 2) single target detection characteristics as a function of input signal-to-noise ratio (SNR); and 3) two target performance characteristics: a) the amplitude of a weaker target as a function of target ratio and target overlap; and b) the detection characteristics of a weaker target as a function of weaker target SNR, strong target SNR, and target overlap.     

自适应增量 Kalman 滤波方法

提出自适应增量Kalman滤波(AIKF)的概念和定义,建立自适应增量Kalman滤波模型及其分析方法,给出主要的计算步骤.传统自适应Kalman滤波(AKF)方法能够对事先未知的系统噪声和量测噪声的统计量进行有效的估计.但是,传统自适应Kalman滤波方法也无法对由于环境因素(如深空探测)的影响、测量设备的不稳定性等原因产生的未知时变测量系统误差进行补偿和校正,从而产生较大的滤波误差,甚至导致发散.提出的自适应增量Kalman滤波方法不但能够对系统噪声和量测噪声的统计量进行估计,而且还能成功消除这种测量系统误差,有效地提高滤波精度.该方法计算简单,便于工程应用.      

Design of a practical tracking algorithm with radar measurements

The extended Kalman filter (EKF) has been widely used as a nonlinear filtering method for radar tracking problems. However, it has been found that if cross-range measurement errors of the target position are large, the performance of the conventional EKF degrades considerably due to nonnegligible nonlinear effects. A new filtering algorithm for improving the tracking performance with radar measurements is developed based on the fact that correct evaluation of the measurement error covariance is possible in the Cartesian coordinate system. The proposed algorithm may be viewed as a modification of the EKF in which the variance of the range measurement errors is evaluated in an adaptive manner. The filter structure facilitates the incorporation of the sequential measurement processing scheme, and this makes the resulting algorithm favorable to both estimation accuracy and computational efficiency. Computer simulation results show that the proposed method offers superior performance in comparison to previous methods. Moreover, our developed algorithm provides some useful insight into the radar tracking problem     

Efficient wideband jammer ing when using stretch processing

Techniques are described for performing adaptive jammer ing over extremely wide bandwidths on radar systems which use linear frequency modulated (LFM) waveforms and stretch processing. It is assumed that the range uncertainty of the target is a small percentage of the equivalent range extent of the uncompressed pulse. The assumption allows the cancellation to take place following stretch processing in either the time domain using a narrowband sliding filter that keeps up with the chirp fate or in the frequency domain. The new approach supports ing performance over gigahertz of bandwidth comparable to that previously achieved over a few megahertz using approximately the same number of spatial degrees of freedom.     

智能桨叶的实时模型与复合自适应振动控制

研究了智能桨叶的实时模型、控制方法与控制器的实时实现。首先,采用MX滤波器实现了对桨叶动态特性的实时在线模拟,给出了该滤波器的系数与所描述的受控结构模态参数之间的相互关系。接着,提出了一种新的复合自适应控制方法,它综合了自适应前馈控制和反馈控制的特点,实现了对桨叶阻尼和振动响应的控制。最后,在所建立的以高速信号处理器为中心的实时数字仿真系统上,实现了对单频、双频及变频、变幅值谐和激励下桨叶振动的控制,获得了良好的振动控制效果。     

一种基于特征空间的自适应天线旁瓣相消算法

把常规自适应天线旁瓣相消算法和特征空间技术相结合,提出了一种新的自适应天线旁瓣相消算法。该算法把常规自适应天线旁瓣相消算法的权矢量向由干扰特征矢量组成的干扰子空间投影,避免了由小特征值对应特征矢量组成的噪声子空间对权矢量的影响,与常规自适应天线旁瓣相消算法相比,该算法具有更好的干扰对消性能,其输出干扰对消比和波束方向图都能在很少的快拍下收敛。计算机仿真结果证实了这种算法的有效性。