Mr. Michael J. Thompson Profile

Michael J. Thompson

Electronics Engineer at Naval Research Lab

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Publications (3)

Proceedings Article | 17 May 2006 Paper

Measures of effectiveness for analysis of radar pulse train deinterleavers

Michael Thompson, Samuel Lin, John Sciortino

Proceedings Volume 6235, 62351I (2006) https://doi.org/10.1117/12.663904

KEYWORDS: Distance measurement, Radar, Analytical research, Mahalanobis distance, Neural networks, Fuzzy logic, Defense and security, Vegetation, Evolutionary algorithms, Statistical analysis

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This paper will compare the various methods of analyzing the results of radar pulse train deinterleavers. This paper is divided into three sections. The first section of this paper will describe the basic methods, such as the confusion matrix, and some measures that can be obtained from the matrix. The measures will include correct correlation, miscorrelation, ambiguity and track purity. Correct correlation is calculated by dividing the total number of correctly clustered pulses by the total number of pulses in the collect. Miscorrelation measures the fraction of received pulses that incorrectly deinterleaved. Ambiguity measures the fraction of received pulses that are rejected by the deinterleaver as having uncertain association with a ground truth track. Track purity measures the ability of the deinterleaver to create a constructed track comprised of pulses from a single ground truth track. These metrics will show the quality of the deinterleaving operation. The second section of this paper will describe some of the advanced similarity measures of effectiveness. This section will also describe how distance measures will be used to analyze deinterleaver results. The two main similarity measures to be discussed in this paper will be the Rand Adjust and Jaccard coefficient. These similarity measures are also known as criterion indices and are used for evaluating the capacity to recover true cluster structure. The reason for the selection of the Jaccard and Rand Adjust as measures is that they both allow a value to be obtained that is between 0 and 1 that will show how good the clusterer in question has performed. The Rand Adjust also allows for more variability in the range between 0 and 1 and appears to provide a more accurate evaluation of the cluster. The distance measures that will be described include Euclidean, Mahalanobis and Minkowski distances. These distance measures have different methods to evaluate each cluster for purity. These measures will provide an indication of the quality of the deinterleaver operation. The third section of this paper will provide the results from these measures on a deinterleavered dataset and will discuss the comparison of these metrics.

Proceedings Article | 17 May 2006 Paper

Comparison of time of arrival vs. multiple parameter based radar pulse train deinterleavers

Samuel Lin, Michael Thompson, Stephen Davezac, John Sciortino

Proceedings Volume 6235, 62351K (2006) https://doi.org/10.1117/12.665044

KEYWORDS: Radar, Fuzzy logic, Neurons, Neural networks, Algorithms, Evolutionary algorithms, Algorithm development, Electronic support measures, Analytical research, Warfare

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Proceedings Article | 9 August 2004 Paper

Analysis of complex radar data sets using fuzzy adaptive resonance theory map

Michael Thompson, John Sciortino

Proceedings Volume 5429, (2004) https://doi.org/10.1117/12.541302

KEYWORDS: Fuzzy logic, Radar, Evolutionary algorithms, Neural networks, Algorithms, Binary data, Analytical research, Algorithm development, Analog electronics, Warfare

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