Canonical transform for tracking with kinematic models

A canonical transform is presented that converts a coupled or uncoupled kinematic model for target tracking into a decoupled dimensionless canonical form. The coupling is due to non-zero off-diagonal terms in the covariance matrices of the process noise and/or the measurement noise, which can be used to model the coupling of motion and/or measurement between coordinates. The decoupled dimensionless canonical form is obtained by simultaneously diagonalizing the noise covariance matrices, followed by a spatial-temporal normalization procedure. This canonical form is independent of the physical specifications of an actual system. Each subsystem corresponding to a canonical coordinate is characterized by its process noise standard deviation, called the maneuver index as a generalization of the tracking index for target tracking, which characterizes completely the performance of a steady-state Kalman filter. A number of applications of this canonical form are discussed. The usefulness of the canonical transform is illustrated via an example of performance analysis of maneuvering target tracking in an air traffic control (ATC) system.     

A Performance Measure for Evaluating Aircraft Landing Trajectories

A general performance index is developed for evaluating aircraft landing trajectories. The primary term in the index is the effect of noise on people residing near the air terminal. Other terms included are passenger comfort, fuel consumed, and the time spent in the near-terminal area. Models are developed for aircraft engine noise, passenger comfort, the population distribution about a specific airport, and the aircraft flight behavior. While this performance index may be used in computing optimal trajectories, it is also useful for comparing nonoptimal trajectories which, for one reason or another, may be worthy of consideration. Some examples of such comparisons are included through simulations of landing. The aircraft considered is a Boeing 737.     

High dynamic output feedback robust control of cascaded extended state observer

High dynamic tracking performance is a key technical index of hydraulic flight motion simulator(HFMS). However, the strong nonlinearities, various model uncertainties and measurement noise in hydraulic actuation systems limit the high dynamic performance improvement. In this paper, the outer axis frame of a HFMS is taken as a case study and its nonlinear dynamic model with consideration of strong nonlinearities, matched and mismatched uncertainties is established.A novel cascaded extended state ...     

A recursive multiple model approach to noise identification

Correct knowledge of noise statistics is essential for an estimator or controller to have reliable performance. In practice, however, the noise statistics are unknown or not known perfectly and thus need to be identified. Previous work on noise identification is limited to stationary noise and noise with slowly varying statistics only. An approach is presented here that is valid for nonstationary noise with rapidly or slowly varying statistics as well as stationary noise. This approach is based on the estimation with multiple hybrid system models. As one of the most cost-effective estimation schemes for hybrid system, the interacting multiple model (IMM) algorithm is used in this approach. The IMM algorithm has two desirable properties: it is recursive and has fixed computational requirements per cycle. The proposed approach is evaluated via a number of representative examples by both Monte Carlo simulations and a nonsimulation technique of performance prediction developed by the authors recently. The application of the proposed approach to failure detection is also illustrated     

用最优控制理论设计双作用叶片泵定子曲线

将最优控制理论应用于双作用叶片泵定子过渡曲线的设计中，提出了一个主要考虑叶片泵寿命、振动与噪声的性能指标泛函，通过计算获得了在该性能指标下的最优过渡曲线，与高次方多项式过渡曲线相比，使得引起泵振动和噪声的度跃动值下降了１８％，在其它性能上该过渡曲线也有不同程度的改善     

Limitations of radiometer performance in spherically invariantnoise

The radiometer is a common method for detection of unknown signals in noise. Most analyses of radiometer performance are based on assumptions of stationary Gaussian noise with known marginal statistics. In this note, we use a spherically invariant noise model to derive simple expressions for radiometer performance degradation in noise variance uncertainty. Numerical examples are provided to show that channel uncertainty imposes a substantial penalty in detection performance     

Effects of CW Interference on Narrow-Band Second-Order Phase-Lock Loops

This paper describes an experimental study of the effect of continuous wave (CW) interference and white noise on a second-order phase-lock loop. The reciprocal of the loop mean-square phase error is used as an index of performance, and the effect of interference levels that do not cause cycle skipping or loss of lock is described in terms of this index. Loop thresholds are determined by measurement of cycle-skipping rates. Stationary or slowly-sweeping CW interference caused a degradation in loop threshold of roughly 3 dB for every 6 dB of interference power above the noise power level. The effective loop signal-to-noise ratio was decreased approximately 1 dB at interference-to-noise power ratios of -3 dB. Interference levels equal to the signal level consistently caused loss of lock, regardless of the loop signal-to-noise ratio.     

包含乘性噪声自适应修正的非合作目标相对导航算法

无人机（UAV）态势感知的任务是利用机载传感器对未知环境进行目标识别和引导,针对无人机与非合作目标间中远距离的相对导航问题,提出了一种基于角度和距离量测的相对状态估计算法。在现有滤波算法的基础上,为了提高精度和稳定性,本文利用了列文伯格-马夸尔特（LM）优化的思想对迭代卡尔曼滤波（IEKF）算法进行改进,提出了一种LM-IEKF算法,并推导该算法在迭代过程中的状态更新方程及协方差阵的递推公式。在此基础上,考虑到距离传感器由于信号相关特性而引入的乘性噪声,现有的加性噪声模型难以适应,因此,进一步提出了基于量测噪声自适应修正的Modified LM-IEKF方法,通过在线实时更新噪声阵提高滤波的精度,并设置渐消记忆指数平滑估计结果。算法验证结果表明,与现有的EKF、IEKF算法相比,在仅含加性噪声的情况下,LM-IEKF算法具有更好的性能;在包含乘性噪声的情况下,Modified LM-IEKF可以有效地估计量测噪声,与目前广泛使用的EKF算法相比,在综合相对位置和相对速度精度上分别提高了10%和23%。     

Detection performance in K-distributed and correlatedRayleigh clutters

Performance prediction for a detection system employing noncoherent integration is carried out for a chi-square family of fluctuating targets in K-distributed clutter plus noise. The detection performance for Swerling 11 targets in the K-distributed clutter plus noise is compared with that in exponentially correlated Rayleigh clutter. The results show that the performance prediction based on N pulses integrated in clutter plus noise using the K-distributed clutter model may be approximately equivalent to that using the exponentially correlated Rayleigh-distributed clutter model     

多传感器目标检测的性能评估（一）

通过对传感器性能分析，将ROC曲线予以量化，根据其几何意义导出传感器探测性能的评估模型，该模型是一个单一的量化指标，用观测量的概率均值和方差来评估传感器性能的优劣。     

基于声学黑洞效应的直升机驾驶舱宽带降噪

声学黑洞（ABH）效应是利用结构阻抗的变化，使结构中传播的波相速度和群速度发生变化，在结构局部区域实现波的聚集，进而通过少量阻尼将能量耗损。该方法具有高效、轻质、宽频等优点，为结构振动噪声控制提供了新的思路，具有较强的潜能和应用前景。本文针对直升机驾驶舱复杂的噪声问题，根据噪声源和传递路径，提出基于ABH效应的内嵌式和附加式2种减振降噪设计方案。利用有限元软件建立了结构声振耦合模型，分析了直升机驾驶舱模型的声振特性，解释了ABH效应有助于降低舱室噪声的机理，并搭建了实验平台，开展了效果测试和性能评估。结果表明，内嵌式ABH结构可以有效降低舱内的中高频噪声，而低频控制能力略显不足。附加式ABH结构可以弥补这一局限性，拓宽有效频带。结合内嵌式和附加式ABH 2种控制方案，相比传统结构在总质量不增加甚至略有降低的前提下，舱室平均噪声水平在1/3倍频程内降低3~10 dB。该研究成果有助于推进ABH新技术在未来直升机工程减振降噪中的应用。     

Adaptive cubature Kalman filter with the estimation of correlation between multiplicative noise and additive measurement noise

Mobile robots are often subject to multiplicative noise in the target tracking tasks, where the multiplicative measurement noise is correlated with additive measurement noise. In this paper,first, a correlation multiplicative measurement noise model is established. It is able to more accurately represent the measurement error caused by the distance sensor dependence state. Then, the estimated performance mismatch problem of Cubature Kalman Filter(CKF) under multiplicative noise is analyzed. An i...     

Performance of a Two-Sample Mann-Whitney Nonparametric Detector in a Radar Application

The detection of signals in an unknown, typically non-Gaussian noise environment, while attempting to maintain a constant false-alarm rate, is a common problem in radar and sonar. The raw receiver data is commonly processed initially by a bank of frequency filters. The further processing of the outputs from the filter bank by a two-sample Mann-Whitney detector is considered. When the noise statistics in all filters are identical, the Mann-Whitney detector is distribution free, i. e., the false-alarm probability may be prescribed in advance regardless of the precise form of the noise statistics. The primary purpose of this paper is to demonstrate the potential advantage of nonparametric detectors over conventional detectors. The signal detection performance of the Mann-Whitney detector is compared to that of an ordinary linear envelope detector plus integrator in the presence of Gaussian and several hypothetical forms of non-Gaussian noise. This comparison is made for both uniform and nonuniform distributions of noise power across the filter bank. Besides providing a much more constant false-alarm rate than the conventional detector, the Mann-Whitney detector's signal detection performance is found also to be much less sensitive to the form of the noise statistics. In one case, its detection sensitivity is found to be 11 dB better than that of the conventional detector. Even when the noise power density is made moderately nonuniform across the filter bank, the detection performance of the Mann-Whitney detector is found not to be significantly affected.     

A nonlinear IMM algorithm for maneuvering target tracking

In target tracking, the measurement noise is usually assumed to be Gaussian. However, the Gaussian modeling of the noise may not be true. Noise can be non-Gaussian. The non-Gaussian noise arising in a radar system is known as glint noise. The distribution of glint noise is long tailed and will seriously affect the tracking performance. We develop a new algorithm that can effectively track a maneuvering target in the glint environment The algorithm incorporates the nonlinear Masreliez filter into the interactive multiple model (IMM) method. Simulations demonstrate the superiority of the new algorithm     

Probability hypothesis density filter with adaptive parameter estimation for tracking multiple maneuvering targets

The probability hypothesis density (PHD) filter has been recognized as a promising tech-nique for tracking an unknown number of targets. The performance of the PHD filter, however, is sensitive to the available knowledge on model parameters such as the measurement noise variance and those associated with the changes in the maneuvering target trajectories. If these parameters are unknown in advance, the tracking performance may degrade greatly. To address this aspect, this paper proposes to incorporate the adaptive parameter estimation (APE) method in the PHD filter so that the model parameters, which may be static and/or time-varying, can be estimated jointly with target states. The resulting APE-PHD algorithm is implemented using the particle filter (PF), which leads to the PF-APE-PHD filter. Simulations show that the newly proposed algorithm can correctly identify the unknown measurement noise variances, and it is capable of tracking mul-tiple maneuvering targets with abrupt changing parameters in a more robust manner, compared to the multi-model approaches.     

一种二维耦合模型机动目标跟踪算法

针对雷达跟踪固定翼飞机的单目标跟踪问题,提出了一种新的二维耦合运动模型。该方法把切向加速度和法向加速度作为状态变量,给出了切向加速度和法向加速度为常值时解析计算状态转移的方法。该模型可以较好地一步预测目标加速度的变化,而且法向和切向加速度的过程噪声可以分别设置。利用该耦合模型的滤波方法,显著地改善了滤波效果,尤其是对加速度的估计。     

Discriminator Detection of Wide-Band PCM/FM

The performance of discriminator detection of wide-band PCM/FM is investigated. Formulas are derived that allow one to predict system performance with the effects of both predetection and postdetection filtering accounted for. In particular, for a postdetection equivalent noise bandwidthbit time product b0T=2, it is shown that best results are obtained with a modulation index ?=0.6. Furthermore, it is shown that performance to within 1.5 dB of theoretical can be obtained.     

Feedback median filter for robust preprocessing of glint noise

Glint noise may arise in a target tracking system. The non-Gaussian behavior of glint noise can severely degrade the tracking performance. Measurement preprocessing at the front-end of the tracker is an effective method to reduce glint noise. The preprocessor proposed by Hewer, Martin, and Zeh (1987), which used the computationally intensive M-estimator, may not be suitable for practical implementation. An alternative method employing the median filter is studied here. The median filter is well known for its simplicity and robustness. However, the efficiency of the median filter can be seriously degraded if input samples are not identically distributed. This is what we may encounter in the tracking problem. A feedback median filter is then proposed to overcome this impediment without substantially increasing complexity. Simulations show that the new preprocessor can greatly improve tracking performance in the glint noise environment.     

Detection Performance of the Cell Averaging LOG/CFAR Receiver

The cell averaging LOG/CFAR receiver is a special implementation of a constant-false-alarm-rate (CFAR) receiver in which the noise level estimate is derived from a set of contiguous time samples of the output of a logarithmic (LOG) detector as obtained from a tapped delay line. This CFAR receiver is capable of operating over a larger dynamic range of noise levels than a conventional cell averaging CFAR receiver, but with somewhat poorer detectability. The performance in stationary Gaussian noise of the cell averaging LOG/CFAR receiver with no post-detection integration is determined in this paper. For a small number of reference noise samples, results were obtained by a Monte Carlo simulation using the technique of importance sampling. For a large number of reference noise samples, a second moment analysis gave the desired results. Both these results can be summarized in the following simple formula, NLOG = 1.65NLIN - 0.65, which relates the number of reference samples required by each of the two receivers for equivalent performance. Thus, for the cell averaging LOG/CFAR receiver to give the same detection performance as the conventional cell averaging CFAR receiver, the number of reference noise samples has to be increased by up to 65 percent.