Optimal speckle reduction in polarimetric SAR imagery

Speckle is a major cause of degradation in synthetic aperture radar (SAR) imagery. With the availability of fully polarimetric SAR data, it is possible to use the three complex elements (HH, HV, VV) of the polarimetric scattering matrix to reduce speckle. The optimal method for combining the elements of the scattering matrix to minimize image speckle is derived, and the solution is shown to be a polarimetric whitening filter (PWF). A simulation of spatially correlated, K-distributed, fully polarimetric clutter is then used to compare the PWF with other, suboptimal speckle-reduction methods. Target detection performance of the PWF, span, and single-channel |HH|² detectors is compared with that of the optimal polarimetric detector (OPD). A novel, constant-false-alarm-rate (CFAR) detector (the adaptive PWF) is as a simple alternative to the OPD for detecting targets in clutter. This algorithm estimates the polarization covariance of the clutter, uses the covariance to construct the minimum-speckle image, and then tests for the presence of a target. An exact theoretical analysis of the adaptive PWF is presented; the algorithm is shown to have detection performance comparable with that of the OPD     

Identification of rational transfer function from frequencyresponse sample

A method for identifying a transfer function, H(z)=A(z)/B(z), from its frequency response values is presented. Identifying the transfer function involves determining the unknown degrees and coefficients of the polynomials A(z) and B( z), given the frequency response samples. The method for finding the parameters of the transfer function involves solving linear simultaneous equations only. An important aspect of the method is the decoupled manner in which the polynomials A(z) and B(z) are determined. The author presents two slightly different derivations of the linear equations involved, one based on the properties of divided differences and the other using Vandermonde matrices or, equivalently, Lagrange interpolation. A matrix synthesized from the given frequency response samples is shown to have a rank equal to the number of poles in the system     

Optimum gain control for A/D conversion using digitized I/Q data inquadrature sampling

Calculation of optimum gain for minimum distortion due to A/D (analog-to-digital) conversion requires the estimation of the input signal strength. To use a common AGC (automatic gain control) for both the I/Q (in-phase and quadrature) signals, it is efficient to estimate the input signal strength using the quantized A/D output from both channels. Assuming a Gaussian input, the relationship between σ of the input of the A/D converter and E(|x|+|y|) and E(max(|x|,|y|)+1/2 min (|x|,|y|)) for t quantized I/Q output x and y is derived. Numerical results obtained using the derived expression and the statistical data obtained through simulation show excellent agreement. It is concluded that, because of its simplicity, the cubic equation obtained by fitting the numerical results should be useful     

Nonparametric rank detectors on quantized radar video signals

Uniform randomization of ties is required for defining distribution-free ranks of independent and identically distributed quantized samples. Formulas of rank probabilities are given and applied to radar detection under quantized video samples. For some detectors, and assuming Gaussian noise, the asymptotic loss L_∞(q) is calculated versus the normalized quantization step q, and the loss L(q) is estimated by Monte Carlo simulations. Both of these resulted in monotonic functions of q (0<q<1.1) that are independent of the other parameters. Furthermore, L(q)≈L_∞(q )⩽0.45 dB, as q<0.8. The quantization step q is normalized with respect to the noise standard deviation     

CCRS C/X-airborne synthetic aperture radar: An Rand D tool for the ERS-1 time frame

The airborne synthetic-aperture radar (SAR) system developed for the Canada Centre for Remote Sensing (CCRS) is described. It consists of two radars, at C-band and X-band. Each radar incorporates the following features: dual-channel receivers and dual-polarized antennas; a high quality, 7-look, real-time processor; a sensitivity time control for range-dependent gain control; a motion-compensation system for antenna steering in azimuth and elevation; and baseband I and Q signal phase rotation. The system also uses a high-power transmitter with a low-power back-up. The SAR maps to either side of the aircraft, at high or low resolution, at incidence angles which in high resolution span 0° to 80°. Radar operating parameters, data products, key specifications and the motion compensation scheme used are presented. Properties of the real-time imagery are discussed and examples of C-band SAR data in the three operating modes are given     

Cascaded detector for multiple high-PRF pulse Doppler radars

A postdetection design methodology for a multiple high-pulse-repetition frequency (PRF) pulse Doppler radar has been developed. The postdetection processor consists of an M out of N detector where range and target ambiguities are resolved, followed by a square-law detector which enhances the minimum signal-to-noise (S/N) power-ratio per pulse burst performance. For given probabilities of false alarm and detection, formulas are derived from which the three thresholds associated with the cascaded detector can be found. Fundamental tradeoffs between the minimum S/N required, number of ghosts, and the number of operations (NOPs) that the cascaded detector must perform are identified. It is shown that the NOPs and the number of ghosts increase and the minimum S/N required decreases as the binary M out of N detector passes more detections to the square-law detector     

Detectability of signals in Laplace noise

Closed-form expressions for the false-alarm and detection probabilities attained by the optimum and the linear detectors of a positive signal in n independent samples of noise having a bilateral exponential or Laplace distribution require lengthy computation when n is large, and those for the optimum detector suffer from round-off error because their terms alternate in sign. It is shown how the method of saddlepoint integration can be conveniently applied to compute these probabilities, and numerical comparisons of the accuracies of the methods are presented. The relative efficiency of the two detectors is calculated as a function of n and found to approach the asymptotic value of 2 very slowly     

The autocorrelation of m-sequences over nonprime finitefields

Nonbinary m-sequences (maximal length sequences) for spread-spectrum communication systems that have a two-level autocorrelation are presented. The autocorrelation function of an m -sequence over the Galois field of q elements GF(q), where q=p^k, for p a prime and k an integer greater than 1, is developed and shown to be bilevel when the elements of GF(q) are expressed as elements of a vector space over the pth roots of unity     

On the uniform sampling of a sinusoidal signal

It is generally accepted that a monochromatic signal such as sin 2πWt (W>0) must be sampled at a uniform rate greater than the ostensible Nyquist rate of 2W samples per to effect a reconstruction of the signal. It is shown that a sinusoid of frequency W Hz is completely determined by its samples taken at the uniform rate of 2r samples per second, where r>0 is arbitrary subject only to the restriction that W ≠kr for any positive integer k. In particular, a pure sinusoid may be sampled uniformly without loss of information at arbitrarily small rates     

A parallel square-root algorithm for modified extended Kalmanfilter

A parallel square-root algorithm and its systolic array implementation are proposed for performing modified extended Kalman filtering (MEKF). The proposed parallel square-root algorithm is designed based on the singular value decomposition (SVD) and the Faddeev algorithm, and a very large scale integration (VLSI) systolic array architecture is developed for its implementation. Compared to other square root Kalman filtering algorithms, the proposed method is more numerically stable. The VLSI architecture described has good parallel and pipelining characteristics in applying to the MEKF and achieves higher efficiency. For n-dimensional state vector estimations, the proposed architecture consists of O(2n²) processing elements and uses O ((s+17)n) time-steps for a complete iteration at each instant, in contrast to the complexity of O((s+6) n³) time-steps for a sequential implementation, where s≈log n     

Periodic ambiguity function of CW signals with perfect periodicautocorrelation

A periodic ambiguity function (PAF) is discussed which describes the response of a correlation receiver to a CW signal modulated by a periodic waveform, when the reference signal in the receiver is constructed from an integral number N, of periods T, of the transmitted signal. The PAF is a generalization of the periodic autocorrelation function, to the case of non-zero Doppler shift. It is shown that the PAF of N periods is obtained by multiplying the PAF of a single period by the universal function sin(Nπν T)/N sin(πνT), where ν is the Doppler shift, to phase-modulated signals which exhibit perfect periodic autocorrelation when there is no Doppler shift. The PAF of these signals exhibits universal cuts along the delay and Doppler axes. These cuts are functions only of t, N and the number M, the modulation bits in one period     

Finding the best set of K paths through a trellis withapplication to multitarget tracking

A solution is presented to the problem of finding the best set of K completely unmerged paths through a trellis with M _i⩾K states at depth i in the trellis, i=0, 1, 2, . . ., N. Here, `best set' means that the sum of the metrics of all K paths in the set is minimized, and `completely unmerged' means that no two paths pass through a common state. The solution involves using the Viterbi algorithm on an expanded trellis. This result is then used to separate the tracks of K targets optimally in a simplified model of a multitarget radar system. The model includes measurement errors and false alarms, but it does not include the effects of missing detections or merged measurements     

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.     

Some practical strategies for reducing intermodulation in satellitecommunications

Various heuristic procedures for obtaining practical solutions to the general one-level carrier frequency assignment problem are described. The problem treated is general in the sense that it accommodates the case where L of the N slots may be explicitly designated as prohibited and unavailable for assignment. This problem occurs in satellite transmission with many small carriers accessing the same transponder where, due to multipath and TV interference from crosspolarized transponders of the same satellite and from copolarized transponders of the adjacent satellites, some portions of the bandwidth of the considered transponder cannot be used. To permit comparison with respect to the intermodulation advantage and central-processing-unit time required, the case without prohibited slots is considered. The sequential insertion procedure in which, starting with two carriers at the two end slots, one additional carrier at a time is optimally inserted into one of the unassigned slots is found best when the ratio between the available bandwidth and the total carrier bandwidth is greater than about 125%. All the heuristic procedures produced assignments whose intermodulation advantages are all greater than the bandwidth ratio     

Resolution Limits with Propagation Phase Errors

Resolution limits and corresponding optimum linear apertures are determined in the presence of phase errors. Let ?(t) be the phase aberration at position t across the aperture; it is assumed that the random process ? has a power law structure function, E{[(?(t)-?(?)]2}= c|t-?|n. Beam tilting caused by the phase error is "removed" (for each sample of ?), then resolution formulas are developed. An approximate analysis is obtained in closed form and yields an optimum resolution proportional to c1/n for O < n < 2. The exact analysis is given for Gaussian ?, and again the optimum resolution is proportional to c1/n. In applications n= 5/3 is of interest, and in the Gaussian case the best obtainable equivalent rectangle resolution is ? ?)/2? (0.975)c3/5 radians with a corresponding optimum linear aperture of 14c-3/5. When long exposures are considered, imaging without removing beam tilting is of interest, and resolution is degraded by a factor of about 2.5 for a linear aperture. Alternatively, in some applications optimum focus as well as beam tilt should be considered, in this case resolution is improved by a factor of about 1.4 (again for n= 5/3). Finally, joint (tilt corrected) optimization over aperture length and taper is treated; however, as one might expect, the use of taper offers negligible resolution improvement.     

Distribution of general noncentral positive definite quadratic formin K-dimensions

The authors present a series solution using Hermite polynomials to the long-standing problem of computing the probability P that positive definite noncentral quadratic form d(x) of a Gaussian random vector x∈R satisfies d( x)⩽r² for any given r∈R. This problem has wide applications in radar, tracking, air traffic control, etc. The fast-converging series solution presented is very accurate and can be performed rapidly using the recursion relations for Hermite polynomials     

Decentralized CFAR signal detection

The authors develop the theory of CA-CFAR (cell-averaging constant false-alarm rate) detection using multiple sensors and data fusion, where detection decisions are transmitted from each CA-CFAR detector to the data fusion center. The overall decision is obtained at the data fusion center based on some k out of n fusion rule. For a Swerling target model I embedded in white Gaussian noise of unknown level, the authors obtain the optimum threshold multipliers of the individual detectors. At the data fusion center, they derive an expression for the overall probability of detection while the overall probability of false alarm is maintained at the desired value for the given fusion rules. An example is presented showing numerical results     

Tracking multiple targets with correlated measurements andmaneuvers

The problem of tracking N targets with correlation in both measurement and maneuver statistics is solved by transforming to a coordinate frame in which the N targets are decoupled. For the case of N identical targets, the decoupling is shown to coincide with a transformation to a set of nested center-of-mass coordinates. Absolute and differential tracking accuracies are compared with suboptimal results to show the improvement that is achieved by properly exploiting the correlation between targets     

CFAR data fusion center with inhomogeneous receivers

Detection systems with distributed sensors and data fusion are increasingly used by surveillance systems. A system formed by N inhomogeneous constant false alarm rate (CFAR) detectors (cell-averaging (CA) and ordered statistic (OS) CFAR detectors) is studied. A recursive formulation of an algorithm that permits a fixed level of false alarms in the data fusion center is presented, to set the optimum individual threshold levels in the CFAR receivers and the optimum `K out of N' decision rule in order to maximize the total probability of detection. The algorithm also considers receivers of different quality or with different communication channel qualities connecting them with the fusion center. This procedure has been applied to several hypothetical networks with distributed CA-CFAR and OS-CFAR receivers and for Rayleigh targets and interference, and it was seen that in general the fusion decision OR rule is not always the best     

A divide and conquer approach to least-squares estimation

The problem of estimating parameters &thetas; which determine the mean μ(&thetas;) of a Gaussian-distributed observation X is considered. It is noted that the maximum-likelihood (ML) estimate, in this case the least-squares estimate, has desirable statistical properties but can be difficult to compute when μ(&thetas;) is a nonlinear function of &thetas;. An estimate formed by combining ML estimates based on subsections of the data vector X is proposed as a computationally inexpensive alternative. The main result is that this alternative estimate, termed here the divide-and-conquer (DAC) estimate, has ML performance in the small-error region when X is appropriately subdivided. As an example application, an inexpensive range-difference-based position estimator is derived and shown by means of Monte-Carlo simulation to have small-error-region mean-square error equal to the Cramer-Rao lower bound