Relative bearing estimation from commodity radios

Dantu, Karthik; Goyal, Prakhar; Sukhatme, Gaurav S.

doi:10.1109/robot.2009.5152689

Cited by 16 publications

(9 citation statements)

References 28 publications

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“…While the concepts proposed in some of these references can be applied to the specific problem of seeking an RF source, we find that exploiting the properties of the RF field and the sensing architecture gives us substantial benefits. Closer to our work, in [6], the motion of a mobile robot is utilized along with an omni-directional radio to estimate the RSS gradient by taking signal strength measurements at a sequence of locations. This method depends on the mobile robot to accurately know its position relative to the starting point of the gradient measurement and also relies on monotonicity and symmetry of the signal strength decay as a function of distance between transmitter and receiver which may be problematic under multi-path scenarios.…”

Section: Avionics Podmentioning

confidence: 99%

RF source-seeking by a micro aerial vehicle using rotation-based angle of arrival estimates

Venkateswaran

Isaacs

Fregene

et al. 2013

2013 American Control Conference

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Abstract-We investigate a computationally and memory efficient algorithm for radio frequency (RF) source-seeking with a single-wing rotating micro aerial vehicle (MAV) equipped with a directional antenna. The MAV is assumed to have no knowledge of its position and to have only an estimate of orientation through a magnetometer. A key novelty of our approach is in exploiting the rotation of the MAV and the directionality of its RF antenna to derive estimates of the angle of arrival (AOA) at each rotation. The MAV then follows the estimated direction until the next rotation is complete. We prove convergence of this greedy algorithm under rather weak assumptions on the noise associated with the AOA estimates, using recent results on the property of recurrence for systems governed by stochastic difference inclusions. These convergence results are supplemented by simulations quantifying the amount of excess travel, relative to the straight line distance to the source. Indoor experiments using Lockheed Martin's Samarai MAV demonstrate the efficacy of the greedy algorithm both for static source-seeking, and for the more challenging problem of tracking a moving source.

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Section: Avionics Podmentioning

confidence: 99%

RF source-seeking by a micro aerial vehicle using rotation-based angle of arrival estimates

Venkateswaran

Isaacs

Fregene

et al. 2013

2013 American Control Conference

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“…This means extra effort in terms of software and hardware and should be avoided especially in static sensor networks, where the position is determined only once after the deployment. One way to overcome this problem is to use a mobile beacon with known position as proposed in [8], [3], [16] and [9]. The advantages of this approach are its scalability and the low requirements on the static nodes.…”

Section: Related Workmentioning

confidence: 99%

“…The results presented in the paper show huge deviations of up to 160 • . In [16] an omnidirectional antenna is attached to a mobile robot. The robot drives to 9 different positions arranged in a circle and its center and measures the RSSI.…”

Section: Related Workmentioning

confidence: 99%

Wireless node localization based on RSSI using a rotating antenna on a mobile robot

Graefenstein¹,

Albert²,

Biber³

et al. 2009

2009 6th Workshop on Positioning, Navigation and Communication

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Determining the physical location of radio nodes is crucial in a wireless sensor network in order to geo-reference the sensor information. This paper presents a localization technique using a mobile radio node attached to a robot. Its position is given by a real time kinematic (RTK) GPS. We propose a new method to obtain the relative bearing between the mobile and the static node using commodity radio hardware. The method exploits the anisotropy of the antenna gain and is not only more precise than the mapping of the RSSI to distance only, it also allows to monitor the integrity of the measurement. Experimental results in an outdoor environment show a standard deviation of 5 • for the angle of arrival. The applicability of the approach for the localization of static radio nodes is demonstated by means of a particle filter. The mean error of the position for experimental data is approximately 13 cm.

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“…While [1] uses an actuated parabolic reflector to estimate the DOA, [2] infers the DOA by rotating the antenna around a signalblocking obstacle and choosing the direction in which the signal was most attenuated. In other related work, [3] uses a WMR equipped with an omnidirectional antenna to estimate the RSS gradient by measuring the power at many locations.…”

Section: Introductionmentioning

confidence: 99%

Quadrotor control for RF source localization and tracking

Isaacs

Quitin

Carrillo

et al. 2014

2014 International Conference on Unmanned Aircraft Systems (ICUAS)

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Abstract-Preliminary results on quadrotor control strategies enabling omnidirectional radio frequency (RF) sensing for source localization and tracking are discussed. The use of a quadrotor for source localization and tracking requires a tight coupling of the attitude control and RF sensing designs. We present a controller for tracking a ramp reference input in yaw (causing rotation of quadrotor) while maintaining a constant altitude hover or translation. The ability to track a ramp in the yaw angle is crucial for RF bearing estimation using received signal strength (RSS) measurements from a directional antenna as it avoids the need for additional gimbaling payload. This bearing or angle of arrival (AOA) estimate is then utilized by a particle filter for source localization and tracking. We report on extensive experiments that suggest that this approach is appropriate even in complex indoor environments where multipath fading effects are difficult to model.

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Relative bearing estimation from commodity radios

Cited by 16 publications

References 28 publications

RF source-seeking by a micro aerial vehicle using rotation-based angle of arrival estimates

RF source-seeking by a micro aerial vehicle using rotation-based angle of arrival estimates

Wireless node localization based on RSSI using a rotating antenna on a mobile robot

Quadrotor control for RF source localization and tracking

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