Statistical Analysis of Ground Clutter from FM Based Passive Radar
- Authors: Bhatta A.1, Pidanic J.2, Mishra A.K.1
- 
							Affiliations: 
							- University of Cape Town
- University of Pardubice
 
- Issue: Vol 62, No 8 (2019)
- Pages: 391-399
- Section: Article
- URL: https://journal-vniispk.ru/0735-2727/article/view/177346
- DOI: https://doi.org/10.3103/S0735272719080028
- ID: 177346
Cite item
Abstract
Statistical characterization of ground clutter information for radar systems is a topic that requires a detailed understanding. In this work, we characterize the ground clutter information from data captured by two Frequency Modulation (FM) based passive radar systems placed at different locations in the Czech Republic. Since the target models are statistically defined by the Swerling models, each of which is based on a particular distribution, we attempted to connect the ground clutter with some of the known distributions. The analysis is performed in three steps. The empirical distribution is fitted with some of the well-known distributions. Two different goodness-of-fit tests (named chi-squared test and Kolmogorov-Smirnov test) are performed on the obtained data by comparing the empirical distribution with the fitted distributions to determine which distribution is the best fit. The observations are analyzed and the results are considered in detail.
About the authors
A. Bhatta
University of Cape Town
							Author for correspondence.
							Email: bhattaabhishek0@gmail.com
				                					                																			                												                	South Africa, 							Cape Town						
J. Pidanic
University of Pardubice
							Author for correspondence.
							Email: Jan.Pidanic@upce.cz
				                					                																			                												                	Czech Republic, 							Pardubice						
A. K. Mishra
University of Cape Town
							Author for correspondence.
							Email: amit.mishra@uct.ac.za
				                					                																			                												                	South Africa, 							Cape Town						
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