A Propagation Environment Modeling in Foliage
1 Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX 76019-0016, USA
2 Air Force Research Laboratory/HEX, Brooks City Base, San Antonio, TX 78235, USA
EURASIP Journal on Wireless Communications and Networking 2010, 2010:873070 doi:10.1155/2010/873070Published: 21 March 2010
Foliage clutter, which can be very large and mask targets in backscattered signals, is a crucial factor that degrades the performance of target detection, tracking, and recognition. Previous literature has intensively investigated land clutter and sea clutter, whereas foliage clutter is still an open-research area. In this paper, we propose that foliage clutter should be more accurately described by a log-logistic model. On a basis of pragmatic data collected by ultra-wideband (UWB) radars, we analyze two different datasets by means of maximum likelihood (ML) parameter estimation as well as the root mean square error (RMSE) performance. We not only investigate log-logistic model, but also compare it with other popular clutter models, namely, log-normal, Weibull, and Nakagami. It shows that the log-logistic model achieves the smallest standard deviation (STD) error in parameter estimation, as well as the best goodness-of-fit and smallest RMSE for both poor and good foliage clutter signals.