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UID:863@lincs.fr
DTSTART;TZID=Europe/Paris:20241211T140000
DTEND;TZID=Europe/Paris:20241211T150000
DTSTAMP:20241216T153607Z
URL:https://www.lincs.fr/events/line-cox-processes-part-ii-large-scale-aut
 omotive-radar-networks-and-statistics-of-successive-successful-detection/
SUMMARY:Line Cox Processes Part II: Large Scale Automotive Radar Networks
 and Statistics of Successive Successful Detection
DESCRIPTION:Note: Part I of this talk was presented at LINCS in 2023
 (www.lincs.fr/events/seminar-talk-by-gourab-ghatak/).\n\n\n\nIn this talk\,
 first\, we revisit the newly introduced model -the binomial line Cox
 processes (BLCP) and discuss its validity from the perspective of real
 world street data. Then\, we employ the BLCP and the Poisson line Cox
 process (PLCP) to emulate a large scale automotive radar network. We will
 briefly discuss the classical stochastic geometry metrics of detection
 probability and the meta-distribution.\n\nThen\, we introduce a novel
 metric for stochastic geometry based analysis of automotive radar networks
 called target tracking probability. Unlike the well-investigated detection
 probability (often termed as the success or coverage probability in
 stochastic geometry)\, the tracking probability characterizes the event of
 successive successful target detection with a sequence of radar pulses.
 From a theoretical standpoint\, this work adds to the rich repertoire of
 statistical metrics in stochastic geometry. To optimize the target tracking
 probability in high interference scenarios\, we study a block medium access
 control (MAC) protocol for the automotive radars and recommend the optimal
 MAC parameter for a given vehicle and street density. Importantly\, we show
 that the optimal MAC parameter that maximizes the detection probability may
 not be the one that maximizes the tracking probability. Our research
 reveals how the tracking event can be naturally mapped to the quality of
 service (QoS) requirements of latency and reliability for different
 vehicular technology use-cases. This can enable use-case specific adaptive
 selection of radar parameters for optimal target tracking.
CATEGORIES:Seminars,Youtube
LOCATION:Amphi 6\, 19 Place Marguerite Perey\, Palaiseau\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=19 Place Marguerite Perey\,
 Palaiseau\, France;X-APPLE-RADIUS=100;X-TITLE=Amphi 6:geo:0,0
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TZID:Europe/Paris
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DTSTART:20241027T020000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
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