Emulating random process target statistics (using MSF)

The topics of matrix spectral factorization (MSF) in conjunction with results from realization theory are applied here in simulating a stationary multi-input/multi-output (MIMO) linear system from a specified power spectral density matrix. MSF provides the appropriate transfer function matrix and realization theory specifies the corresponding parameters of a linear system having this transfer function This approach can be used to correctly capture the cross correlations that exist in a multichannel vector random process (representing a particular radar target signature). Aspects of the solution to this problem are illustrated using an original representative example problem with a closed-form answer. Existing software programs for accomplishing MSF are identified and one has been successfully validated using the known closed-form solution mentioned above. A streamlined realization algorithm (offered here as the primary theoretical contribution) can be used along with the MSF computer program and can now be applied to actual radar data. Besides multichannel spectral estimation, several other important applications of this same MSF solution methodology are summarized in Appendix B including extending applicability to the complex case (to handle radar polarization issues related to coherent phase processing), and finally in reexpressing second order statistics of a multichannel autoregressive moving average (ARMA) process as those of a simpler but mathematically equivalent autoregressive (AR) process of slightly higher dimensions (as another original application of the same major result offered here)     

Synthetic Aperture Radar

The general theory of side-looking synthetic aperture radar systems is developed. A simple circuit-theory model is developed; the geometry of the system determines the nature of the prefilter and the receiver (or processor) is the postfilter. The complex distributed reflectivity density appears as the input, and receiver noise is first considered as the interference which limits performance. Analysis and optimization are carried out for three performance criteria (resolution, signal-to-noise ratio, and least squares estimation of the target field). The optimum synthetic aperture length is derived in terms of the noise level and average transmitted power. Range-Doppler ambiguity limitations and optical processing are discussed briefly. The synthetic aperture concept for rotating target fields is described. It is observed that, for a physical aperture, a side-looking radar, and a rotating target field, the azimuth resolution is ?/? where ? is the change in aspect angle over which the target field is viewed, The effects of phase errors on azimuth resolution are derived in terms of the power density spectrum of the derivative of the phase errors and the performance in the absence of phase errors.     

VSAR: a high resolution radar system for ocean imaging

The velocity synthetic aperture radar (VSAR) is a conceptual synthetic aperture radar (SAR)-based sensor system for high resolution ocean imaging. The VSAR utilizes data collected by a multielement SAR system, to extract information not only about the radar reflectivity of the observed area, but also about the radial velocity of the scatterers in each pixel. This is accomplished by making use of the phase information contained in multiple SAR images, and not just the magnitude information as in conventional SAR. Using this velocity information, the VSAR attempts to compensate for the velocity distortion inherent in conventional SAR and to reconstruct the ocean reflectivity. We present the basic theory of the VSAR system and its performance. We also provide an analysis of the VSAR imaging mechanism for a statistical model of the radar returns, designed to capture the effects of speckle and of resolution degradation due to the decorrelation of the radar returns     

Optimum Signals for High-Resolution Radio Transmission Systems

This paper reports on progress in signal design that has led to improvedresolution capability in radar and communication systems without theuse of complicated signal-processing techniques.Two approaches to the problem of improving resolution capabilityare made. The first approach emphasizes the need to produce sharplypeaked autocorrelation functions. The optimum signal amplitude infrequency is specified to accomplish this, and the spectral density ofthe deterministic signal is shown to satisfy a homogeneous Wiener-Hopfequation. The second approach emphasizes the need to producelow and flattened cross-correlation functions, in order to distinguishthem (since they correspond to error outputs) from the sharply peakedautocorrelation functions. With the use of stationary phase integration,a detailed method for producing any desired cross-correlationamplitude is presented. In particular, the techniques necessary to producesinusoidally modulated cross-correlation functions are discussed.These tools are applied to a realistic N-signal processing system,and the resulting optimum signals are shown to be amplitude-modulatedchirped sinusoids. Detailed examples for physically justifiablesystem parameters are included.     

运动补偿用惯性器件误差对SAR成像分辨率的影响研究

 为提高合成孔径雷达（SAR）系统的性价比,必须根据SAR成像分辨率的要求和整体系统参数,设计相应精度的运动补偿用捷联惯导系统。在确定SAR运动补偿系统方案和安装方式的基础上,分析不同方向的加速度计和陀螺仪误差对天线相位中心位置测量误差的影响,并利用位置测量误差与SAR成像分辨率之间的关系,进一步明确了不同方向的加速度计和陀螺仪对SAR成像分辨率的影响。研究表明：基于SAR的工作原理和安装方式,x方向加速度计和y方向陀螺仪对SAR成像分辨率的影响明显比其他惯性器件严重;相同误差水平的惯性器件对SAR成像分辨率的影响随着合成孔径时间和工作波长的不同而不同,时间越长,波长越短,影响则越严重。SAR成像仿真证明了结论的正确性。研究结果对于研制高性价比SAR成像运动补偿系统有一定的理论指导意义。     

Digital synthetic aperture radar processing via optical computers

A method for performing digital phase history processing of synthetic aperture radar (SAR) data using optical computers is proposed. The method has nothing in common with the old analog optical SAR processing methods (which used lenses), but is rather a totally digital (numerical) technique for computing the individual complex pixel values based on matrix-vector multiplications. The method can be expected to greatly increase the potential processing speed and coverage possibilities of high-resolution digital SAR systems     

An improved imaging algorithm for spaceborne MAPs sliding spotlight SAR with high-resolution wide-swath capability

Conventional synthetic aperture radar(SAR) systems cannot achieve both highresolution and wide-swath imaging simultaneously.This problem can be mitigated by employing multiple-azimuth-phases(MAPs) technology for spaceborne sliding spotlight SAR systems.However, traditional imaging algorithms have met challenges to process the data accurately, due to range model error, MAPs data reconstruction problem, high-order cross-coupling phase error and variation of Doppler parameters along the azimuth direction.Therefore, an improved imaging algorithm is proposed for solving the above problems.Firstly, a modified hyperbolic range equation(MHRE) is proposed by introducing a cubic term into the traditional hyperbolic range equation(THRE).And two curved orbit correction methods are derived based on the proposed range model.Then, a MAPs sliding spotlight data reconstruction method is introduced, which solves the spectral aliasing problem by a de-rotation operation.Finally, high-order cross-coupling phases and variation of Doppler parameters are analyzed and the corresponding compensation methods are proposed.Simulation results for point-target scene are provided to verify the effectiveness of the proposed algorithm.     

Trajectory deviations in airborne SAR: analysis and compensation

This paper concerns the analysis and compensation of trajectory deviations in airborne synthetic aperture radar (SAR) systems. Analysis of the received data spectrum is carried out with respect to the system geometry in the presence of linear, sinusoidal, and general aircraft displacements. This shows that trajectory deviations generally produce spectral replicas along the azimuth frequency that strongly impair the quality of the focused image. Based on the derived model, we explain the rationale of the motion compensation (MOCO) strategy that must be applied at the SAR processing stage in order to limit the resolution loss. To this end aberration terms are separated into range space invariant and variant components. The former can be accounted for either in a preprocessing step or efficiently at range compression stage. The latter needs a prior accommodation of range migration effect. We design the procedure for efficient inclusion of the MOCO within a high precision scaled FT based SAR processing algorithm. Finally, we present results on simulated data aimed at validating the whole analysis and the proposed procedure     

Coherent spatial filtering for SAR detection of stationary targets

Analysis of UHF synthetic aperture radar (SAR) images has revealed a spatially correlated phase structure over a resolved target such as a long wire or a large truck. This phase variation, approximated by a simple, range-dependent factor 4πr/λ, results in a line-shaped image spatial spectrum. Such image phase and spectral features can be exploited by coherent spatial filtering to improve target-to-clutter ratios of large targets and stationary target detectability in a strong clutter environment     

Analysis of foliage-induced synthetic pattern distortions

Phase and amplitude fluctuations induced by wave propagation through foliage limit the ability of a synthetic aperture radar (SAR) system to image a target under foliage. One-way measurements of these fluctuations were done at C-, L-, UHF band during the July 1990 Foliage Penetration Experiment using single frequency CW signal sources and the NASA/JPL SAR receiver. The phase and amplitude data are coherently integrated to create the synthetic azimuthal patterns that would result when attempting to image a point target obscured by foliage. The effect of synthetic aperture length frequency, and polarization on the attenuation and azimuthal response of foliage obscured targets is investigated     

Localization of step changes in multitemporal SAR images

Deals with multitemporal sequences of synthetic aperture radar (SAR) images with regions possibly affected by step reflectivity patterns of change. Specifically, it addresses the problems of detecting a temporal step pattern with small reflectivity change against a constant pattern and of estimating the transition instant for the step. The statistically optimized signal processing techniques proposed in this work are most appropriate for the new generation of SAR systems with high revisit time that are currently under development. We propose two different techniques, based on the maximum likelihood (ML) approach, that make different use of prior knowledge on the radar cross section (RCS) levels of the searched pattern. They process the whole sequence to achieve optimal discrimination capability between regions affected and not affected by a step change and optimal estimation accuracy for the step transition instant. The first technique (known step pattern (KSP)-detector) assumes complete knowledge of the RCS levels of the searched pattern of change, while the second one (USP-detector) is based on the assumption of totally unknown step pattern.     

Time-frequency hop codes based upon extended quadratic congruences

Time-frequency hop codes are developed that can be used for coherent multiuser echolocation and asynchronous spread spectrum communication systems. They represent a compromise between Costas codes, which have nearly ideal autoambiguity but not so good cross-ambiguity properties, and linear congruential codes, which have nearly ideal cross-ambiguity but unattractive autoambiguity properties. Extended quadratic congruential code words are shown to have reasonably good autoambiguity and cross-ambiguity properties across the whole class of code sets considered. A uniform upper bound is placed on the entire cross-ambiguity function surface, and bounds are placed on the position and amplitude of spurious peaks in the autoambiguity function. These bounds depend on the time/bandwidth product and code length exclusively and lead naturally to a discussion of the design tradeoffs for these two parameters. Examples of typical autoambiguity and cross-ambiguity functions are given to illustrate the performance of the new codes     

An Upper Bound on Detection Probability for Fluctuating Signals

In the theory of signal detectability, the signal-to-noise ratio (SNR), defined as the quotient of the average received signal energy and the spectral density of the white Gaussian noise, is a fundamental parameter. For a signal which is exactly known, or known except for a random phase, this ratio uniquely defines the detection performance which can be achieved with a matched filter receiver. However, when the signal amplitude is a random parameter, the detection performance is changed and must be determined from the probability density function (pdf) of the amplitude. Relative to the case of a constant signal amplitude, such signal amplitude fluctuation usually degrades performance when a high probability of detection (Pd) is required, but improves performance at low values of Pd; the corresponding change in the required SNR is the so-called signal fluctuation loss Lf. Thus, since Lf in some cases represents an improvement in performance for low values of Pd, a question of at least theoretical interest is: how large might this improvement be, when the class of all signal amplitude pdf's is considered. The solution, presented here, results in a lower bound on the signal fluctuation loss Lf as a function of Pd, or equivalently an upper bound on Pd as a function of SNR. The corresponding most favorable pdf was determined using the Lagrange multiplier technique and results of a numerical maximization are included to provide insight into the general properties of the solution.     

Advances in non-linear apodization

Selected new methods and applications of non-linear apodization for irregularly-shaped and parse coherent apertures and arrays are presented. The benefits include unproved impulse response performance, i.e., reduced peak sidelobes and integrated sidelobe power, along with improved mainlobe resolution, compared to classic windowing techniques. Nonlinear apodization (NLA) techniques can also serve as powerful engines for effective superresolution and bandwidth extrapolation of coherent data for filling sparse apertures. The sparse aperture filling property of superresolution algorithms for radar data forms the basis for a new concept which is introduced here: synthetic multiple aperture radar technology (SMART). Increased swath and/or reduced antenna size are some of the benefits postulated for SMART applied to synthetic aperture radar (SAR) systems. The benefits of these new methods and applications for nonlinear apodization are then demonstrated for two specific applications: 1) sidelobe control for Y-type synthetic aperture radiometers, such as the European Soil Moisture and Ocean Salinity (SMOS) system (Kerr et al.) and JPL's proposed GeoSTAR (Lambrigsten) concept; and, 2) filling of sparse synthetic aperture radar data by exploiting the bandwidth extrapolation properties of nonlinear apodization based superresolution techniques. The methods that have been developed and demonstrated herein have potential application to a wide range of passive and active microwave remote sensing and radar systems.     

A Model for Generating Synthetic VHF SAR Forest Clutter Images

We propose a model for generating low-frequency synthetic aperture radar (SAR) clutter that relates model parameters to physical characteristics of the scene. The model includes both distributed scattering and large-amplitude discrete clutter responses. The model also incorporates the SAR imaging process, which introduces correlation among image pixels. The model may be used to generate synthetic clutter for a range of environmental operating conditions for use in target detection performance evaluation of the radar and automatic target detection/recognition algorithms. We derive a statistical representation of the proposed clutter model's pixel amplitudes and compare with measured data from the CARABAS-II SAR. Simulated clutter images capture the structure and amplitude responses seen in the measured data. A statistical analysis shows an order of magnitude improvement in model fit error compared with standard maximum-likelihood (ML) density fitting methods.     

离散系统LMI滤波技术

给出了一种离散系统最优滤波器的线性矩阵不等式（ＬＭＩ）设计方法。在系统干扰噪声能量有界情况下,将有约束的滤波问题转换为无约束的最优状态估计问题。利用ＬＭＩ方法给出了最优无偏滤波器存在的充分必要条件,所得滤波器的阶数小于系统状态个数。将ＬＭＩ方法应用于飞机飞行试验数据处理中,分析了实际飞行条件下飞机运动的模型,并对该模型进行扩展线性化处理,得到了一个较易实现的ＬＭＩ滤波算法。仿真结果表明,所提出的算     

High-resolution SAR imaging with angular diversity

We propose to use the APES (amplitude and phase estimation) approach for the spectral estimation of gapped data and synthetic aperture radar (SAR) imaging with angular diversity. A relaxation-based algorithm, referred to as GAPES (Gapped-data APES), is proposed, which includes estimating the spectrum via APES and filling in the gaps via a least squares (LS) fitting. For SAR imaging with angular diversity data fusion, we perform one-dimensional (1-D) windowed fast Fourier transforms (FFTs) in range, use the GAPES algorithm to interpolate the gaps in the aperture for each range, apply 1-D inverse FFTs (IFFTs) and dewindow in range, and finally apply the two-dimensional (2-D) APES algorithm to the interpolated matrix to obtain the 2-D SAR image. Numerical results are presented to demonstrate the effectiveness of the proposed algorithm     

Computer Simulation of Synthetic Aperture Radar Images of Three-Dimensional Objects

A digital simulation of coherent synthetic aperture radar (SAR) images of three-dimensional objects is described. The simulation is intended to produce representative SAR images that would be suitable for image analysis and pattern recognition studies. The procedure involves a modeling of the object using a combination of three-dimensional quadratic shapes yielding a smooth surface representation. The radar images of these models are then computed using physical optics scattering theory. Finite resolution both in range and cross-range direction is incorporated via a theoretical analysis which results in a simple Fourier transform representation of an equivalent "offset" window filter. Examples of the computer simulation for both infinite resolution and blurred or finite resolution are given for a KC-135 aircraft model.