Cost‐effective, asynchronous inter‐sensor distance estimation using trigonometry

Yoon, Jong Wan; Park, H.; Kim, N.S.; Park, T.

doi:10.1049/el.2016.0442

Cited by 1 publication

(1 citation statement)

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“…After building the graph according to the sequence in Figure 5, it is found that the graph is in the form of a logarithmic model. The logarithmic regression equations as given by the author in [25,26] can be defined in a general form of (1).…”

Section: Regression Analysismentioning

confidence: 99%

Wireless sensor network calibration technique for low-altitude unmanned aerial vehicle localization in paddy field

2021

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This paper presents the use of the received signal strength indicator (RSSI) from the RF signal to estimate the distance from a point where the signal is transmitted to the point where the signal is received. This can be a challenge as in the paddy field, the watery and dry conditions, as well as the height of the paddy plant can affect signal transmission during this estimation process. Two low-cost ground beacons, Beacon1 and Beacon2 (The coordinator), are used and placed in a known location with a fixed distance across the paddy field, which becomes the reference point during the distance estimation for the unmanned aerial vehicle (UAV). These signals are analyzed by using the non-right-angle trigonometry computation, to estimate the distance between the transmitter and the receiver. The estimated distance is compared with the measured value to determine the efficiency of this approach. The calibration trendlines of these beacons in the open, watery and dry paddy fields are discussed and presented. It is found that the dry paddy field gives less RSSI mean error and proved that humidity can contribute to the distance estimation error.

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Section: Regression Analysismentioning

confidence: 99%