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Proceedings Paper

Measures of effectiveness for analysis of radar pulse train deinterleavers
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Paper Abstract

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.

Paper Details

Date Published: 17 May 2006
PDF: 9 pages
Proc. SPIE 6235, Signal Processing, Sensor Fusion, and Target Recognition XV, 62351I (17 May 2006); doi: 10.1117/12.663904
Show Author Affiliations
Michael J. Thompson, Naval Research Lab. (United States)
Samuel Lin, Naval Research Lab. (United States)
John C. Sciortino, Naval Research Lab. (United States)


Published in SPIE Proceedings Vol. 6235:
Signal Processing, Sensor Fusion, and Target Recognition XV
Ivan Kadar, Editor(s)

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