A RCS model of complex targets for radar performance prediction

Minna Vaila, Juha Jylha, Ville Väisänen, Henna Perala, Ari Visa, Mikko Harju, Kai Virtanen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

8 Citations (Scopus)


The objective of the radar performance prediction is to compute quantities of interest concerning the ability of the radar to observe its surroundings. Besides the properties of the radar system, the performance is affected by the target, whose radar cross section (RCS) is one of the predominant factors. The performance prediction is usually performed in relation to the target RCS characterized by a constant value or a particular statistical distribution. Such representations generalize real-life complex targets rendering them unsuitable for some objectives since the RCS is significantly influenced by the target aspect angle and is inherently stochastic by nature. Thus, a more dynamic description may be valuable e.g. for analyzing the radar performance on a flight path of interest. We propose representing the RCS with a histogram that includes such dynamic properties and is suitable for considering the target in different ways for performance prediction: in a more general manner or dependent on its aspect angle. We consider the case of traditional RCS with low spatial resolution and demonstrate the proposed approach through the probability of detection computed for a generic surveillance radar.

Original languageEnglish
Title of host publication2017 IEEE Radar Conference, RadarConf 2017
Number of pages6
ISBN (Electronic)9781467388238
Publication statusPublished - 7 Jun 2017
MoE publication typeA4 Conference publication
EventIEEE Radar Conference - Seattle, United States
Duration: 8 May 201712 May 2017


ConferenceIEEE Radar Conference
Abbreviated titleRadarCon
Country/TerritoryUnited States


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