Stanislav Kesler

Bias and resolution of the MUSIC and the modified FBLP algorithms in the presence of coherent plane waves

A study of the characteristics of the MUSIC and the modified forward-backward linear prediction (MFBLP) methods of angle-of-arrival estimation, in terms of their sample bias and resolution in the fully correlated signal environment, is presented. Using Monte Carlo simulations, it is shown that the MFBLP algorithm has better capability in resolving two fully correlated signals than the spatially smoothed MUSIC algorithm. >

Resolving uncorrelated and correlated sources by linear prediction

The resolution and the estimation error are investigated for two linear prediction (LP) algorithms for bearing estimation with uniform linear array of sensors, in the presence of incoherent and coherent sources: the Burg algorithm (BA) and the generalized Burg algorithm (GBA). The superresolution is easily achieved with both algorithms when the sources are incoherent. For coherent sources, however, the BA estimate is somewhat more sensitive to the magnitude and the phase of the intersignal correlation than the GBA, thereby resulting in the increased error in the bearing estimates.

A solution for self-calibrating a large distorted phased array using subarray processing

Two subarray procedures are added to the multiple scatterer algorithm (MSA) for the purpose of self-calibrating a large distorted phased array. Depending on whether or not overlapping between adjacent subarrays exists, they are called the multiple scatterer algorithm with subarray processing (MSA-S) or the multiple scatterer algorithm with overlapping subarray processing (MSA-OS). These are tested using experimental microwave echoes from an industrial site and a housing development area. The data sets are obtained using an X-band (3-cm), 83-m phased array. MSA-OS can synthesize a specular-like beamformer using the echoes from three low-quality beamformers, each of which is incapable of phase-cohering the array by itself. MSA is found to be superior to the more basic dominant scatterer algorithm (DSA), and MSA-OS is found to perform the best. >

Adaptive change detection in image sequence

Two adaptive algorithms are presented for the detection of small changes in a pair of images in a low signal to clutter plus noise ratio (SCNR) environment. They both have the ability to track the nonstationary image signals and suppress the clutter plus noise background. Both detectors are based on the adaptive correlation canceling technique. One algorithm uses an order recursive least squares (ORLS) lattice filter, while the other is based on the two-dimensional least mean square (TDLMS) algorithm. The only a priori information required by the algorithms is that the background clutter plus noise in the pair of images is spatially correlated. An analytical expression for the improvement factor for the change detectors is presented. The performance of the two algorithms is evaluated by using an optical satellite image, with computer generated target and noise added.<<ETX>>

Target classification using radar data: a comparative study

This paper compares three different approaches when used against a problem of present and practical interest: the classification of radar return data from two classes of aircraft. The three approaches are: the typical feature extraction approach used for target classification when dealing with radar data; a multi layer perceptron neural network approach and; a branched multi layer perceptron neural network approach. The comparison was performed under equal conditions and at restricted sensor parameter conditions to demonstrate the anticipated advantage of the neural network approach in that it will be able to classify targets when the sensor parameters are not suitable for the feature extraction approach to work. The classification rate was used as the measure of effectiveness. Up to date the feature extraction approach has provided a classification rate of 84.1%. The multi layer perceptron consists of a one hidden layer network and the best classification rate it has provided is 86.8%. The branched multi layer perceptron consists of two separate multi layer perceptron neural networks trained to recognize only one class of targets and the best classification rate it has provided is 54.9%. The discrepancy in performance between the two neural network approaches is perhaps due to the more general structure with improved discrimination power of the branched network.

Autoregressive detection by generalized Burg algorithm

In the case of nonstationary signal fields, e.g., spatial array beamforming in the presence of correlated multipath, an autoregressive angle estimator should employ the generalized Burg algorithm (GBA) to account for the non-Toeplitz structure of the power cross-spectral density matrix. The detection performance of the GBA is analyzed and is shown to be comparable to the performance of the conventional AR detector in the case where no correlated interference is present.

Sensitivity of the high-resolution eigenanalysis methods to estimated number of sources

INTRODUCTION One of the primary purposes of radar sensor arrays is the determination of hearings of clmely spaced radiating sources. DiEiculties arise when, in addition to direct paths there exist multipath components in the received signal. Multipath components are scaled and delayed replica of the direct signal, propagating a t the same frequency and are fully correlated with the direct received signals.

Resolution of incoherent and coherent sources by autoregressive beamforming

In this paper we investigate the resolution properties of two linear prediction algorithms for bearing estimation with line array of sensors, in the presence of either incoherent or coherent sources: the Burg algorithm and the generalized Burg algorithm. It was demonstrated by computer simulation that both algorithms achieve the superresolution of incoherent sources. For coherent sources, however, it was shown that the Burg estimates are sensitive to the magnitude and the phase of the inter-signal correlation, while the generalized Burg estimates are comparable to those obtained for the incoherent sources and are less sensitive to intersignal correlation.

Resolution of coherent radar targets in the near field of an array antenna

In this paper we present the results of the research on radar target elevation estimation in the near field of the vertical line array antenna. In particular, we examine the case of targets at low elevations where coherent reflections from ground prevent accurate measurements of target angular positions. The estimation method used is a modified version of the MUSIC algorithm, adapted for the application in the near field antenna environment. A spatial smoothing preprocessing scheme has been applied in order to resolve close coherent signals. The algorithm has been successfully applied go both simulated and recorded radar data. Controlled Ku-band radar experiments were conducted at the Valley Forge Research Center of the University of Pennsylvania. Estimation of actual target elevations to within 1 standard beamwidth has been achieved for SNRs of about 0 db.

An exact solution of the analytic equation of image quality from optimum quantization of microwave imaging data

An exact solution is presented of the analytic equation of image quality in terms of the entropy of the quantized aperture data. Previously published work provides an optimum quantization scheme that obtains the best image quality for a given distribution of complex aperture data and a given number of bits into which each complex data sample is to be quantized. An extension is provided to determine the number of bits required of the quantized signal for the image to achieve a given quality or, conversely, what quality of image can be obtained for a given number of quantized levels. It is shown that the theory imposes substantially no constraints on the distributions of amplitude and phase in the microwave data. It is also shown that the optimum quantization design derived from the theory is nearly scene-independent and may achieve real-time performance. >