TY - GEN
T1 - Co-operative estimation for source localisation using binary sensors
AU - Selvaratnam, Daniel D.
AU - Shames, Iman
AU - Dimarogonas, Dimos V.
AU - Manton, Jonathan H.
AU - Ristic, Branko
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/6/28
Y1 - 2017/6/28
N2 - This paper considers the problem of localising a signal source using a team of mobile agents that can only detect the presence or absence of the signal. A background false detection rate and missed detection probability are incorporated into the assumptions. An estimation algorithm is proposed that discretizes the search environment into cells, and uses Bayesian techniques to approximate the posterior probability of each cell containing the source. Analytical results are presented for a range of specific cases, and simulations are used to investigate more complex scenarios.
AB - This paper considers the problem of localising a signal source using a team of mobile agents that can only detect the presence or absence of the signal. A background false detection rate and missed detection probability are incorporated into the assumptions. An estimation algorithm is proposed that discretizes the search environment into cells, and uses Bayesian techniques to approximate the posterior probability of each cell containing the source. Analytical results are presented for a range of specific cases, and simulations are used to investigate more complex scenarios.
UR - http://www.scopus.com/inward/record.url?scp=85046131554&partnerID=8YFLogxK
U2 - 10.1109/CDC.2017.8263875
DO - 10.1109/CDC.2017.8263875
M3 - Conference contribution
T3 - 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
SP - 1572
EP - 1577
BT - 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 56th IEEE Annual Conference on Decision and Control, CDC 2017
Y2 - 12 December 2017 through 15 December 2017
ER -