Optimal sensor configurations for rectangular target detection

Bourque, Francois-Alex; Nguyen, Bao

doi:10.1109/icca.2011.6138087

Cited by 3 publications

(16 citation statements)

References 11 publications

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“…Moreover, if something is intuitive, we can understand it immediately without prior knowledge or training [27], which is similarly defined in other domains as well [28,29]. This is also in accordance with BPMo, since it has been confirmed by existing studies that process diagrams are required to be intuitive and easy to understand [6,8].…”

Section: Intuitive Understandabilitysupporting

confidence: 52%

An empirical investigation of intuitive understandability of process diagrams

Jošt

Huber

Heričko

et al. 2016

Computer Standards & Interfaces

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Section: Intuitive Understandabilitysupporting

confidence: 52%

An empirical investigation of intuitive understandability of process diagrams

Jošt

Huber

Heričko

et al. 2016

Computer Standards & Interfaces

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“…The relationship between these two problems is akin to the difference between the traveling salesman problem and Chinese postman problem [33]. The problem of optimal planning of angles of viewing, or looks of rectangular objects at known location but unknown orientation is investigated in [34].…”

Section: B Uav Path Planningmentioning

confidence: 99%

Sensor-Driven Area Coverage for an Autonomous Fixed-Wing Unmanned Aerial Vehicle

Paull

Thibault

Nagaty

et al. 2014

IEEE Trans. Cybern.

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Area coverage with an onboard sensor is an important task for an unmanned aerial vehicle (UAV) with many applications. Autonomous fixed-wing UAVs are more appropriate for larger scale area surveying since they can cover ground more quickly. However, their non-holonomic dynamics and susceptibility to disturbances make sensor coverage a challenging task. Most previous approaches to area coverage planning are offline and assume that the UAV can follow the planned trajectory exactly. In this paper, this restriction is removed as the aircraft maintains a coverage map based on its actual pose trajectory and makes control decisions based on that map. The aircraft is able to plan paths in situ based on sensor data and an accurate model of the on-board camera used for coverage. An information theoretic approach is used that selects desired headings that maximize the expected information gain over the coverage map. In addition, the branch entropy concept previously developed for autonomous underwater vehicles is extended to UAVs and ensures that the vehicle is able to achieve its global coverage mission. The coverage map over the workspace uses the projective camera model and compares the expected area of the target on the ground and the actual area covered on the ground by each pixel in the image. The camera is mounted on a two-axis gimbal and can either be stabilized or optimized for maximal coverage. Hardware-in-the-loop simulation results and real hardware implementation on a fixed-wing UAV show the effectiveness of the approach. By including the already developed automatic takeoff and landing capabilities, we now have a fully automated and robust platform for performing aerial imagery surveys.

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“…It was found [11][12][13][14] that, for n looks, the optimal search strategies correspond to μ i = i · μ with i = 0, . .…”

Section: Problem Statementmentioning

confidence: 99%

“…Note that P e m, n ð Þis a function of P, Q, and n as revealed in Equation (11), while φ depends only on P and Q as revealed in Equation (12).…”

Section: Imperfect Detection As a Function Of Rangementioning

confidence: 99%

“…Furthermore, the explicit expression for the overall probability of detection can become complicated even when the probability of detection for a single observation is simple and there are few observations. Despite these challenges, Nguyen and Bourque 12 identified non-trivial sets of critical look angles that optimize the probability of detection locally. They successfully determined the one that is maximal in the sense that the corresponding probability of detection is a maximum among the local optima that were considered.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Modeling the expected detection probability for mine countermeasure operations based on cross-section and multiple looks

Nguyen¹,

Mirshak²

2016

Journal of Defense Modeling & Simulation

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We present a methodology to determine the expected probability of detection of a target based on multiple looks or angles: tactics and cross-sections. While previous studies confirm that the general probability of detection improves significantly with the number of looks, our findings demonstrate that this value can vary substantially depending on search and detection tactics, as well as the target's cross-section. We argue that the angular dependence of the detection process is often overlooked for search and detection missions, but that this can be elegantly accounted for when assuming symmetrical targets. Consequently, we investigate three tactics where each look is independent: first, a globally optimal tactic where all look angles are equally spaced; second, a tactic which distributes the look angles randomly; and third, a tactic which imposes the same angle for all look angles. We are also able to use the first tactic to extract the guaranteed best angle of the broad side of a target, and additionally for each tactic we propose an example of a corresponding search pattern. We hope that our findings in this paper increase awareness within the search and detection community of the phenomenologies of multiple looks, and that our presented methodology can be incorporated into the mine search and detection tactics.

show abstract

Optimal sensor configurations for rectangular target detection

Cited by 3 publications

References 11 publications

An empirical investigation of intuitive understandability of process diagrams

An empirical investigation of intuitive understandability of process diagrams

Sensor-Driven Area Coverage for an Autonomous Fixed-Wing Unmanned Aerial Vehicle

Modeling the expected detection probability for mine countermeasure operations based on cross-section and multiple looks

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