Proportional Tracking with Clipped-input Matched Filters

A proportional boresight-error measurement is described for tracking systems that is applicable to envelope-producing matched filters with hard-limited inputs. The error response is derived as a function of input SNR and the filter output SNR is estimated.     

Simple Tracking Filters: Closed-Form Solutions

A closed-form steady-state solution is presented for a three-state tracking filter with continuous position measurements and exponentially correlated target acceleration. Some other related closed-form solutions are discussed, and some comparative performance data is presented for the discrete measurement case.     

A Study on Particle Filters for Single-Tone Frequency Tracking

In this paper, we present an online approach for frequency tracking of a noisy sinusoid using sequential Monte Carlo (SMC) methods, also known as particle filters (PFs). In addition, apart from employing the classical Cartesian formulation model, we also develop two alternative dynamical models, namely, nearly constant frequency (NCF) and Singer, which are adapted from the maneuvering target tracking discipline, to describe the evolution of time-varying frequencies, and investigate their fitness to the frequency tracking application. When compared with conventional techniques whose performance is restricted to linear Gaussian models and/or to slowly varying frequencies, PFs are more flexible to handle situations where these conditions are violated. Extensive evaluations on the proposed new models and PF tracking algorithms are conducted with different sets of frequency inputs and levels of signal-to-noise ratio (SNR). According to the computer simulation results, it is found that PFs under all investigated models consistently outperform and are less sensitive to SNR levels than the extended Kalman filter (EKF). Furthermore, the results suggest that while none of the models perfectly fits all types of frequency inputs, NCF model is more suitable for moderately varying frequencies, whereas the Singer is more suitable for rapidly changing frequencies.     

Heading and Speed Errors for x, y Tracking Filters

Heading and speed errors are analytically determined for noneumavering targets at the output of an x, y tracking filter which processes range and bearing measurements from a radar sensor in a track-while-scan (TWS) operation. These errors are shown to depend upon target range and speed, the angle between the radius and velocity vectors, sensor accuracies, and tracking filter parameters. eters. Depending upon the tracking filter implementation, these errors may also be a function of target bearing.     

探地雷达中目标的自适应检测与跟踪

提出了一种自适应α-β滤波算法，该算法可用于探地雷达对路面结构的自适应检测与分层。仿真实验的结果证明了算法的有效性。     

Correlation Effects of MTI Filters

A frequency domain approach for determining the effective number of independent pulses at the output of a square law detector in a moving target indicator (MTI) system leads to a definition which gives the same asymptotic results as given by a previous definition.     

Simple Tracking Filters: Position and Velocity Measurements

Parametric data is presented showing the effects of combining velocity measurements with the usual position measurements in a simple form of target tracking filter. Effects on steady-state performance and filter gains are shown, as well as data on time required for convergence to steady state.     

Simple Tracking Filters: Steady-State Filtering and Smoothing Performance

Computed data is presented, in normalized form, showing steady-state filtering and smoothing performance for optimum three-state estimators which assume exponentially correlated acceleration of the tracked object. The data are useful for preliminary design, gain selection, and performance prediction.     

Altitude Estimation Using Asynchronous ? - ? Tracking Filters

In the analysis of the ?-? tracking filter it is usually assumed that the tracking filter and data source operate in synchronism at a constant data rate. However, in a multisensor environment in which the tracking algorithm operates at fixed intervals, the tracking filter cannot be synchronized with the sensors. An analytical solution is obtained for the case in which the tracking filter and data source operate asynchronously with a ?time-correction? process used to approximate the synchronous operation of the tracking filter. An example is given in which the effects of data quantization on the performance of an altitude tracking filter for air traffic control are examined. It is shown that the asynchronous operation of the tracking filter in the example without the time-correction process will result in significant errors in the predicted altitude.     

Transient Response of Tracking Filters with Randomly Interrupted Data

The transient responses during the initialization phase of a first-order ?-? tracking filter and a second-order Kalman filter are evaluated as a function of radar measurement accuracy and the probability of receiving valid data at the prescribed intervals. Monte Carlo simulation results are complemented by analysis of the filtering processes and curves are presented which clearly define the deterioration in filter performance attributable to reduced probabilities of data acquisition. In addition, the responses of ?-? and Kalman filters are shown to be identical when the ?, ? gains are selected optimally.     

Detection of Narrowband Signals Using Time-Domain Adaptive Filters

The detection performance of a conventional narrowband analyzer is compared with two adaptive processor mechanizations based on the Widrow least mean squares algorithm. Comparisons are based on both analysis and extensive digital simulation. With a narrowband signal in stationary, white background noise, the performance of the three systems is shown to be essentially the same. With nonstationary background noise, the performance of the conventional system degrades by an amount proportional to the processing time-bandwidth product. The adaptive systems appear to be less sensitive to the nonstationary background, resulting in a potential performance advantage relative to the conventional system.     

基于角速度估计自适应的IMM目标跟踪算法

为了解决目标强机动时目标跟踪算法模型集不匹配的问题,提出了一种基于角速度估计的自适应交互式多模型算法。通过对角速度的估计,在目标的不同运动模式下选取最优模型集,角速度估计精度高时,通过角速度估计值构造模型集,减小模型间竞争;角速度估计精度低时,采用标准IMM算法的模型集,提高模型集的覆盖范围,从而提高跟踪精度。仿真结果表明该方法能够明显提升目标跟踪性能,对强机动目标的跟踪效果尤其显著。     

Maneuvering Target Tracking Using Adaptive State Estimation

Two approaches to a nonlinear state estimation problem are presented. The particular problem addressed is that of tracking a maneuvering target in three-dimensional space using spherical observations (radar data). Both approaches rely on semi-Markov modeling of target maneuvers and result in effective algorithms that prevent the loss of track that often occurs when a target makes a sudden, radical change in its trajectory. Both techniques are compared using real and simulated radar measurements with emphasis on performance and computational burden.     

Adaptive Phased-Array Tracking in ECM using Negative Information

Target tracking with adaptive phased-array radars in the presence of standoff jamming presents both challenges and opportunities to the track filter designer. A measurement likelihood function is derived for this situation which accounts for the effect of both positive and negative contact information. This likelihood function is approximated a? a weighted sum of Gaussian terms consisting of both positive and negative weights, accounting for the positive and negative contact information. Additionally, recent theoretical results have been reported which have derived an accurate measurement error covariance in the vicinity of the jammer when adaptive beamforming is used by the radar to null the effects of the jammer. We compare the impact of using a likelihood function that accounts for negative contact information and the corrected measurement error covariance by comparing five Kalman filter-based trackers in five different scenarios. We show that only those track filters which use both the negative contact information and the corrected measurement error covariance are effective in maintaining track on a maneuvering target as it passes through the jamming region. This approach can also be generalized to any target tracking problem where the sensor response is anisotropic.     

Adaptive Control of a Flexible Beam Using Least Square Lattice Filters

An indirect adaptive control scheme for the control of flexible structures using least square lattice filters for on-line identification of the number of modes, mode shapes, and modal amplitudes is presented. The control law is based on modal pole placement. The system requires on-line validation of the results of the identification scheme before allowing changes in control law parameters. Successful adaptive control is demonstrated using the simulations for the 12 ft free-free beam apparatus at NASA Langley Research Center.     

Adaptive Spacecraft Attitude Tracking Controller Design Based on Similar Skew-symmetric Structure

This article presents an adaptive attitude tracking controller with external disturbances and unknown inertia parameters. The similar skew-symmetric structure is extended from the autonomous case to the non-autonomous case. The non-autonomous similar skew-symmetric is chosen as the desired structure of the closed loop system for attitude controller design. Based on this structure, a novel adaptive backstepping scheme is proposed to design the attitude controller by taking full advantage of the symmetry and the positive definiteness of the inertia matrix. The attitude tracking precision is enhanced by employing the linear parameterized form of the external disturbance torques. Simulation results demonstrate the effectiveness of the proposed attitude controller.     

Optimum Filters for Image Registration

Two-dimensional cross-correlation techniques are applied to the problem of image registration under the assumption of small geometric distortion. Optimum filter functions for use with arbitrary window functions are derived for two performance measures of interest: peak-to-sidelobe ratio, and mean- square registration error; the latter is examined in terms of the contribution due to distortion and the contribution due to noise. A generalized Lagrange multiplier approach is used to derive at least approximate ate solutions to the case where the images are modeled as random processes and to the case where the images are assumed to be deterministic.     

BOC信号的相关跟踪研究及GALILEO接收机设计初探

Galileo卫星导航系统是欧盟组织研发的新一代完全面向民用的卫星导航系统,使用了BOC(二进制副载波)这一独特的调制方式,研究BOC信号的相关峰特性,对设计接收机捕获跟踪通道是至关重要的。本文简要介绍了Galileo系统导航信号的特征和频率规划,对多种BOC信号的自相关性能、码跟踪方法进行了仿真,并探讨了接收机开发中的关键问题。