Optimal polarimetric processing for enhanced target detection

The results of a study of several polarimetric target detection algorithms are summarized. The algorithms were tested using real target-in-clutter data collected by the Lincoln Laboratory 35 GHz synthetic aperture radar (SAR) sensor. Fully polarimetric measurements (HH, HV, VV) are processed into intensity imagery using adaptive and nonadaptive polarimetric whitening filters (PWFs). Then a two-parameter constant false alarm rate (CFAR) detector is run over the imagery to detect the targets. Nonadaptive PWF processed imagery is shown to provide better protection performance than either adaptive PWF processed imagery or single-polarimetric-channel HH imagery. In addition, nonadaptive PWF processed imagery is shown to be visually clearer than adaptive processed imagery     

基于零空间的改进直接分配法

直接分配法是解决操纵面冗余飞行器控制分配的一种有效方法,但直接分配法只能对指定方向上误差最小目标进行优化,这种缺点限制了直接分配法的应用。零空间可以在保持转矩不变的前提下对控制量进行调节,利用这种特性,在三维转矩直接分配的基础上,通过对零空间坐标K进行数学规划可以使其他性能指标达到最优。推导证明,控制量最小问题和阻力最小问题分别可以转化为对坐标K的线性规划与二次规划问题。仿真结果表明,给出的基于零空间的改进直接分配法可以实现控制量最小和阻力最小控制分配。     

正交调制实现窄带带通数字滤波器

为了提高滤波器性能并简化设计,采用正交调制等效结构实现了带通滤波,使一组中心频率不同,而其余指标都相同的窄带带通数字滤波器设计简化为一个窄带低通数字滤波器设计.对窄带低通数字滤波器设计,又采用了多抽样率多级实现技术,提高了运算效率,节省了存储空间.该设计已在TMS320C3X系列DSP芯片上调试通过,并运用于铁路电气化区段机车信号译码.     

On the Design of Suboptimal Controllers for Minimal Time Feedback Regulators

A method for designing suboptimal minimal time controllers for linear, time-invariant regulator systems is presented. An economical closed-loop controller is obtained by using Lyapunov surfaces, corresponding to a quadratic Lyapunov function, as a continuous approximation for isochronal surfaces. Systems employing this controller are obtained by minimization, with respect to parameters of the quadratic Lyapunov function, of the worst case upper bound on the arrival time of an arbitrary initial state at the origin.     

A Comparison of Numerical Methods for Solving Optimal Control Problems

Linear systems with quadratic performance criteria typically lead to two-point boundary value problems. The numerical solution of such problems is often difficult because of roundoff and truncation errors. In this paper numerical methods for digital computer solutions are considered for a system described by a given second-order linear differential equation and the results are compared. The results show that where accurate analytic solutions cannot be obtained, the invariant imbedding technique yields more accurate results, for a given integration grid interval, than the other methods considered.     

计算气动声学中的紧致滤波格式

从理论上分析了数值伪波产生的原因,要消除数值伪波可用滤波方法。为了使滤波器具有理想的截断特性,引入了修正的高斯函数。通过让滤波器的频响函数与修正的高斯函数逼近,利用序列二次规划(SQP)方法优化了五对角紧致滤波格式。优化的滤波格式提高了计算精度和效率,增强了数值稳定性,更易于实施。一维和二维算例体现了优化滤波格式的性能改进。     

LMI approach to the mixed H2/H∞filtering design for discrete-time uncertain systems

The problem of full-order robust filtering design for discrete-time uncertain linear systems is addressed. The uncertain parameters are assumed to belong to convex bounded domains (polytope type uncertainty). The main purpose is to design a stable linear filter such that the filtering error output signal remains bounded. For that, the parameterization of all linear filters assuring quadratic stability with an H_∞ attenuation constraint to the filtering error system is provided in terms of linear matrix inequalities (LMIs). Then, through the definition of an auxiliary cost, an upper bound to the filtering error variance is minimized, providing a mixed H₂/H _∞ guaranteed cost filtering design. Standard optimization procedures with global convergence assured can be used to solve the problem, as illustrated by an example     

基于改进遗传算法的飞行控制律参数设计

在进行大包线飞行控制律设计中,需将飞行包线分为几个区域,针对各个区域设计线性控制律,采用多个线性控制律来近似替代所需的非线性控制律,本文中线性控制律采用PID控制结构,若用传统PID控制律参数整定方法,工作烦琐、设计时间长,而且控制效果不是很好,提出运用遗传算法优化控制律参数,并针对遗传算法局部寻优能力差、收敛速度差、易早熟等缺点,对其进行了几点改进,为提高鲁棒性,对其适应函数进行了设计,针对某机型某个区域的俯仰控制进行了PID控制律设计仿真,利用改进的遗传算法对其参数进行优化,结果表明,该方法在23代就能得到最优控制参数,而且使系统动态性能有了较明显的提高。     

Modeling and a Correlation Algorithm for Spaceborne SAR Signals

A mathematical model of a spaceborne synthetic aperture radar (SAR) response is presented. The associated SAR system performance, in terms of the resolution capability, is also discussed. The analysis of spaceborne SAR target response indicates that the SAR correlation problem is a two-dimensional one with a linear shift-variant response function. A new digital processing algorithm is proposed here in order to realize an economical digital SAR correlation system. The proposed algorithm treats the two-dimensional correlation by a combination of frequency domain fast correlation in the azimuth dimension and a time-domain convolver type of operation in the range dimension. Finally, digitally correlated SEASAT satellite SAR imagery is used in an exemplary sense to validate the SAR response model and the new digital processing technique developed.     

基于ILMI的直升机悬停控制律设计

提出了一种新的直升机悬停控制律设计方法。在建立了直升机数学模型后,通过迭代线性矩阵不等式方法(ILM I)求解基于线性二次型的直升机悬停控制律,使得直升机能达到满意的悬停性能指标,并且明显降低了控制器的保守性。仿真结果表明,使用该方法设计的控制器同时满足动态性能指标和稳态性能指标,与使用标准线性二次型方法设计的控制器相比,其性能指标在横侧向提高了12.3%,纵向提高了13.7%。     

Decentralized reduced-order filters

Continuous and discrete methods of designing simple reduced-order local filters within a large-scale network are suggested. The filters are designed to estimate only the local variables of interest and not the entire state vector. The method has the advantage that one need not know the mathematical models of the subsystems generating the interconnection variables. The order of the filter can be small enough so that there is no computational burden associated with the filter. The disadvantage of the method is that performance is lost by using a reduced-order filter instead of a full-order filter. An example that demonstrates one application in the aerospace industry is presented     

Low-Sensitivity Design of Optimal Linear Control Systems

The quadratic performance criterion, linear optimal control problem is reformulated to incorporate constraints on trajectory sensitivity. The open-loop solution is obtained for sensitivity functions defined for small plant-parameter variations. This approach has provided a beginning for other attempts to solve the low-sensitivity analytical design problem, as reported in the references.     

Correlation Algorithms for Radar Map Matching

The results of a theoretical study of a simple radar edge detection correlation approach are presented. Several candidate edge correlation algorithms are described. Results of a theoretical evaluation of one particular candidate correlation algorithm are presented and verification of the edge correlation concept is provided through a presentation of correlation performance obtained using real radar imagery.     

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.     

Track-to-track fusion with dissimilar sensors

An analysis is described of a kinematic state vector fusion algorithm when tracks are obtained from dissimilar sensors. For the sake of simplicity, it is assumed that two dissimilar sensors are equipped with nonidentical two-dimensional optimal linear Kalman filters. It is shown that the performance of such a track-to-track fusion algorithm can be improved if the cross-correlation matrix between candidate tracks is positive. This cross-correlation is introduced by noise associated with target maneuver that is common to the tracking filters in both sensors and is often neglected. An expression for the steady state cross-correlation matrix in closed form is derived and conditions for positivity of the cross-correlation matrix are obtained. The effect of positivity on performance of kinematic track-to-track fusion is also discussed     

Information Approach to Fixed-Gain Design

A method for designing fixed-gain controllers and filters for systems with large parameter variation is presented. The approach is based on finding the minimax point of the Kullback information measure between the fixed-gain system and the optimal system at a given operating point. The effectiveness of the proposed approach is illustrated by designing a fixed-gain system for the short-period control of a high-performance aircraft and evaluating its performance over the flight envelope.     

The effect of the clutter-to-noise ratio on Doppler filterperformance

The effect of the clutter-to-noise ratio on the performance of a Doppler filter is considered. Clutter is assumed to have a power level which is unknown and varies in range. The assessment of the performance of a Doppler filter is based on the gain of the filter, which is the normalized output signal-to-interference ratio improvement at a given Doppler. The gain is generally a complex function of the statistics of the clutter. New upper and lower bounds on the gain differential between the expected design point clutter-to-noise ratio and the actual clutter-to-noise ratio are found. These bounds are independent of the clutter covariance matrix and are only a function of the unknown clutter-to-noise ratio. The bounds are valid for both Gaussian and non-Gaussian noise and for arbitrary linear filters. The upper and lower bounds differ by the theoretical coherent integration gain, 10 logN dB, where N is the number of pulses. A tighter lower bound is found for the case when the filters are matched filters. A simple exact expression is found for matched filters assuming a Gaussian Markov clutter model as the clutter spectral width approaches zero. An easily implementable adaptive procedure is given which improves performance due to the unknown clutter-to-noise ratio. This work extends a previous result, valid for the Emerson filter, that shows the effect of clutter-to-noise ratio on performance in terms of an average quantity, the improvement factor     

Minimax detection for signals with unknown parameters

Minimax detectors are often used for the detection of signals with unknown parameters in additive white Gaussian noise. Several minimax strategies are discussed for both real and complex signals, including one based on the least favorable distribution of the unknown parameters and a second, distribution-free method based on the worst case parameter values. Also discussed are the relationships between these minimax detectors and equal correlation filters for real signals and equal deflection quadratic detectors for complex signals. Conditions are given under which the two different minimax strategies produce identical detectors     

1种未知输入观测器的推广设计方法

为使未知输入观测器的应用范围更广,提出1种解决在未知输入观测器(UIO)设计过程中对象测量输出线性相关问题的方法。通过对测量输出的线性相关性分析,测量输出可以被合理分组,使得各组内包含部分互相线性无关的测量输出并且保证这些分组涵盖了所有需要诊断的测量输出传感器;以这种方式来满足设计UIO的存在条件,并在此基础上针对不同分组来设计UIO以进行关于传感器的故障诊断算法设计。针对1个工程实例,使用UIO进行传感器的故障诊断设计验证了该方法的可行性。     

Navigation system design using time-varying complementary filters

A new methodology for the design of navigation systems for autonomous vehicles is introduced. Using simple kinematic relationships, the problem of estimating the velocity and position of an autonomous vehicle is solved by resorting to special bilinear time-varying filters. These are the natural generalization of linear time-invariant complementary filters that are commonly used to properly merge sensor information available at low frequency with that available in the complementary region. Complementary filters lend themselves to frequency domain interpretations that provide valuable insight into the filtering design process. This work extends these properties to the time-varying setting by resorting to the theory of linear differential inclusions and by converting the problem of weighted filter performance analysis into that of determining the feasibility of a related set of linear matrix inequalities (LMIs). Using this set-up, the stability of the resulting filters as well as their "frequency-like" performance can be assessed using efficient numerical analysis tools that borrow from convex optimization techniques. The mathematical background that is required for complementary time-varying filter analysis and design is introduced. Its application to the design of a navigation system that estimates position and velocity of an autonomous vehicle by complementing position information available from GPS with the velocity information provided by a Doppler sonar system is described.