Pregled bibliografske jedinice broj: 284719
Unified Bayesian Situation Assessment Sensor Management
Unified Bayesian Situation Assessment Sensor Management // Proceedings of SPIE / Kada, Ivan (ur.).
Bellingham (WA): SPIE, 2005. (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 284719 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Unified Bayesian Situation Assessment Sensor Management
Autori
El-Fallah, Adel ; Zatezalo, Aleksandar ; Mahler, Ronald ; Mehra, K. Rman ; Alford, Mark
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of SPIE
/ Kada, Ivan - Bellingham (WA) : SPIE, 2005
Skup
Defense and Security Symposium 2005
Mjesto i datum
Orlando (FL), Sjedinjene Američke Države, 28.03.2005
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Situation Assessment; Sensor Management; Nonlinear Filtering; Random Sets; Targets of Interest
Sažetak
Sensor management in support of situation assessment (SA) presents a daunting theoretical and practical challenge. We demonstrate new results using a foundational, joint control-theoretic approach to SA and SA sensor management that is based on three concepts: (1) a “ dynamic situational significance map” that mathematically specifies the meaning of tactical significance for a given theater of interest at a given moment ; (2) an intuitively meaningful and potentially computationally tractable objective function for SA, namely maximization of the expected number of targets of tactical interest ; and (3) integration of these two concepts with approximate multitarget filters (specifically, first-order multitarget moment filters and multi-hypothesis correlator (MHC) engines). Under this approach, sensors will be directed to preferentially collect observations from targets of actual or potential tactical significance, according to an adaptively modified definition of tactical significance. Result of testing this sensor management algorithm with significance maps defined in terms of target’ s location, speed, and heading will be presented. Testing is performed against simulated data, and different sensor management algorithms including the proposed are compared.
Izvorni jezik
Engleski
Znanstvena područja
Matematika