| Performance Analysis of the Nonhomogeneity Detector for STAP applications |
MAY 2001 |
5 pages |
| Authors:
Muralidhar Rangaswamy; Braham Himed; James H. Michels; ARCON CORP WALTHAM MA
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 | We consider the statistical analysis of a recently proposed non- homogeneity detector (NHD) for Gaussian interference statistics. We show that a formal goodness-of-fit test can be constructed by accounting for the statistics of the generalized inner product (GIP). Specifically the Normalized-GIP follows a central-F distribution. This fact is used to derive the goodness-of-fit test in this paper. We also address the issue of space-time adaptive processing (STAP) algorithm performance using ... |
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| Covariance Matrix Estimator Performance In Non-Gaussian Spherically Invariant Random Processes. Revision |
JAN 96 |
26 pages |
| Authors:
James H. Michels; ROME LAB ROME NY
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| This report describes the performance of the covariance matrix estimator in non-Gaussian spherically invariant random processes (SIRP). Analytic expressions are derived for the variance of the estimator. Specific consideration is given to the special cases of Weibull and K-distributed processes as a function of the shape parameter. Validation is achieved via Monte-Carlo simulation. The expressions reveal the increase in the estimator variance for non-Gaussian SIRP's as well as the sample ... |
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| Innovations Based Detection Algorithm for Correlated Non-Gaussian Processes Using Multichannel Data |
NOV 93 |
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| Authors:
Muralidhar Rangaswamy; James H. Michels; ROME LAB GRIFFISS AFB NY
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 | This report addresses the problem of multichannel signal detection in additive, correlated, non-Gaussian noise using the innovations approach. While this problem has been addressed extensively for the case of additive Gaussian noise, the corresponding problem for the non-Gaussian case has received limited attention. This is due to the fact that there is no unique specification for the joint probability density function (PDF) of N correlated non-Gaussian random variables. We overcome ... |
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| Correlation Function Estimator Performance in Non-Gaussian Spherically Invariant Random Processes |
OCT 93 |
32 pages |
| Authors:
James H. Michels; ROME LAB GRIFFISS AFB NY
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| In this report, analytic expressions are developed for the variance, error variance and bias of the time-averaged correlation function estimator for stationary, discrete, non-Gaussian complex processes. The expressions derived here pertain to the general class of non-Gaussian processes known as Spherically Invariant Random Processes (SIRP's) Specific results are shown for K-distributed processes which form a special case of the SIRP's. Furthermore, these equations are derived for the general case of ... |
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| Considerations of the Error Variances of Time-Averaged Estimators for Correlated Processes |
DEC 92 |
113 pages |
| Authors:
James H. Michels; ROME LAB GRIFFISS AFB NY
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| This report considers the sample and error variances of both time- averaged correlation function and parameter estimators for stationary discrete complex processes. Analytic expressions for the variance of the biased, time- averaged auto and cross-channel correlation function estimators of stationary discrete complex processes are developed. These expressions relate the variance of these estimators not only to the size of the observation windows used to obtain the estimates, but also to ... |
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| Multichannel Detection of Partially Correlated Signals in Clutter |
DEC 92 |
53 pages |
| Authors:
James H. Michels; ROME LAB GRIFFISS AFB NY
|
| This report considers the Gaussian multichannel binary detection problem in which the signal and non-white clutter noise are Gaussian vector processes with unknown statistics. A generalized likelihood ratio using multichannel innovations processes is implemented via a model-based approach where the signal and clutter are assumed to be characterized by autoregressive vector processes with arbitrary temporal and cross-channel correlation. The innovations processes are obtained through linear estimation using multichannel parameter estimates. ... |
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| Multichannel Detection Using the Discrete-Time Model-Based Innovations Approach |
AUG 91 |
384 pages |
| Authors:
James H. Michels; ROME LAB GRIFFISS AFB NY
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| This report makes several contributions. First, an approach is developed to synthesize multichannel autoregressive (AR) random processes allowing for the control of temporal and cross-channel correlation of the processes subject to specific constraints for realizable correlation sequences. Second, analytic expressions are developed for the error variance of time- averaged correlation function estimators for discrete, complex baseband processes. These expressions reveal the functional dependence of the error variance, not only on ... |
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| Multichannel Linear Prediction and Its Association with Triangular Matrix Decomposition |
NOV 90 |
37 pages |
| Authors:
James H. Michels; ROME AIR DEVELOPMENT CENTER GRIFFISS AFB NY
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| Much of the existing literature on theory of light scattering from fluctuating media is restricted to either monochromatic incident fields, or to quasimonochromatic incident fields which are spatially coherent over the entire scattering volume. This reprint presents a theory of light scattering from fluctuating media which allows the spectrum and the coherence properties of the incident light to be very general, and which makes less restrictive assumptions about the response ... |
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| Synthesis of Multichannel Autoregressive Random Processes and Ergodicity Considerations |
JUL 90 |
205 pages |
| Authors:
James H. Michels; ROME AIR DEVELOPMENT CENTER GRIFFISS AFB NY
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| In this paper, a method is presented for synthesizing multichannel autogressive random processes. The procedure allows for variable temporal and cross-correlation properties subject to specific constraint conditions for correlation functions. Expressions for the ergodic series are also developed providing a performance measure to specify the sample integration sizes required to achieve a specific variance of the time-averaged correlation function estimates. A unique aspect of this development is the determination of ... |
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| A Parametric Detection Approach Using Multichannel Processes |
NOV 89 |
70 pages |
| Authors:
James H. Michels; ROME AIR DEVELOPMENT CENTER GRIFFISS AFB NY
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| This report considers the binary multichannel detection problem for an unknown random signal vector in additive nonwhite interference plus white Gaussian noise. A generalized likelihood ratio is derived based on the vector error residuals from multichannel prediction error filters designed as minimum mean squared error estiamtes under each hypothesis. The observation processes are considered to have an arbitrary in time and across channels. The report outlines a research investigation currently ... |
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| Laser Backscatter Characteristics of Materials of Interest in Ballistic Missile Defense (BMD), |
JUL 1974 |
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| Authors:
Fred J. Demma; James H. Michels; Eugene Bromley; Albert F. Morreall; ROME AIR DEVELOPMENT CENTER GRIFFISS AFB N Y
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| A series of measurements were conducted on laser backscatter characteristics of materials of interest in Ballistic Missile Defense (BMD). The data taken was reduced for the purposes of describing the reflectance of reentry vehicles (RV), decoy, and tank fragment materials. As evidenced by the experimental data, a wide variety of scattering was encountered from BMD targets. Specifically, whether or not the material was metallic, painted, sealed, overcoated, surface roughed, or ... |
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