Efficient Bayesian methods for updating and storing uncertain search information for UAVs

Flint, Matthew; Fernandez, Emmanuel; Polycarpou, Marios M.

doi:10.1109/cdc.2004.1428838

Cited by 12 publications

(5 citation statements)

References 10 publications

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“…Moreover, it is also known that (28) Now (27) and (28) Using (14) and (30) we have (31) ROR maps enter into the set . Here we know that so using (14) we have (32) is exponentially stable in the large w.r.t.…”

Section: Discussionmentioning

confidence: 96%

Stable Cooperative Surveillance With Information Flow Constraints

Gil

Passino

Cruz

2008

IEEE Trans. Contr. Syst. Technol.

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Abstract-We consider a cooperative surveillance problem for a group of autonomous air vehicles (AAVs) that periodically receives information on suspected locations of targets from a satellite and then must cooperate to decide which AAV should search for each target. This cooperation must be performed in spite of imperfect intervehicle communications (e.g., messages with random but bounded delays), less than full communication connectivity between vehicles, uncertainty in target locations, and imperfect vehicle search sensors. We represent the state of the search progress with a "search map," and use an invariant set to model the set of states where there is no useful information on target locations. Arrivals of new suspected target location information from the satellite corresponds to perturbations of the search map from this invariant set. A cooperation strategy that pursues a type of "persistent area denial" will try to force trajectories of the system into the invariant set by exploiting initial target information and search progress by the AAVs. We show that the invariant set is exponentially stable for a class of cooperative surveillance strategies. We provide a comparative analysis of cooperative and noncooperative strategies. Next, we show via simulations the impact of imperfect communications, imperfect vehicle search sensors, uncertainty in search locations, and pop-up suspected locations on performance.

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Section: Discussionmentioning

confidence: 96%

Stable Cooperative Surveillance With Information Flow Constraints

Gil

Passino

Cruz

2008

IEEE Trans. Contr. Syst. Technol.

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“…Another possibility consists in considering the presence of decoys, i.e., objects that can be considered as a true target when seen from a specific point of view. For example, [12] introduces a Bayesian process for cooperative search when the sensors embedded on the UAVs are not able to determine whether a detected target is real or not. In [16], the random finite set probability density is used to model both target-generated observation and false alarms.…”

Section: Related Workmentioning

confidence: 99%

Bounded-error target localization and tracking using a fleet of UAVs

et al. 2021

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“…Then speculates enemy air-defense firepower deployment scenarios and establishes the threat probability model on account of the operational environment [10] .…”

Section: Determinate the Threat Positionmentioning

confidence: 99%

“…In esp. (10), k refers to the intensity coefficient of the threat, which is associated with the threat strength; Pr refers to the power of received signal; σ refers to the RCS (Radar-Cross-Section) of UAV;…”

Section: Simulatingmentioning

confidence: 99%

Autonomous route planning for UAV when threats are uncertain

Zhang

Pei

2014

Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference

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Route planning in 3-D uncertainty environment, especially when the threats are uncertain, is the trend of the UAV (unmanned aerial vehicle) route planning. Against the opacity of enemy threat information, the threat probability model is adopted to determine the location of the threat, and D-S evidence synthesis algorithm is used to determine the threat strength, then to calls D* route planning algorithm getting UAV flight route and forming the "flying, judging and planning" autonomous planning pattern. Paper also analyzes various threats and then establishes 3-D models for these threats. The method turns out to be feasible by simulation.

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Efficient Bayesian methods for updating and storing uncertain search information for UAVs

Cited by 12 publications

References 10 publications

Stable Cooperative Surveillance With Information Flow Constraints

Stable Cooperative Surveillance With Information Flow Constraints

Bounded-error target localization and tracking using a fleet of UAVs

Autonomous route planning for UAV when threats are uncertain

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