Importance sampling simulation techniques applied to estimating false alarm probabilities

Author

Lu, D. ; Yao, K.

Author_Institution

Dept. of Electr. Eng., California Univ., Los Angeles, CA, USA

fYear

1989

Firstpage

598

Abstract

An upper bound on the estimation variance and a lower bound on the improvement ratio (IR) are derived for importance sampling (IS) simulations with multidimensional input processes. Not only can the runs needed for some accuracy and the IR be obtained, but also various suboptimum IS parameters. Simulation and numerical results indicate that this bounding technique is tight and applicable to non-Gaussian clutters

Keywords

clutter; probability; radar theory; signal processing; estimation variance upper bound; false alarm probability estimation; importance sampling simulation techniques; improvement ratio lower bound; multidimensional input processes; nonGaussian clutters; numerical results; radar; suboptimum importance sampling parameters; tight bounding technique; Analytical models; Clutter; Computational Intelligence Society; Digital communication; Error probability; Financial advantage program; Monte Carlo methods; Numerical simulation; Radar theory; Upper bound;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1989., IEEE International Symposium on

Conference_Location

Portland, OR

Type

conf

DOI

10.1109/ISCAS.1989.100423

Filename

100423

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1630774