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Quadcopters are beginning to play an important role in precision agriculture. In order to localize and operate the quadcopter automatically in complex agricultural settings, such as a greenhouse, a robust positioning system is needed. In previous research, we developed a spread spectrum sound-based local positioning system (SSSLPS) with a 20 mm accuracy within a 30 × 30 m greenhouse area. In this research, a noise tolerant SSSLPS was developed and evaluated. First, the acoustic noise spectrum emitted by the quadcopter was documented, and then the noise tolerance properties of SSSounds were examined and tested. This was done in a greenhouse with a fixed quadcopter (9.75 N thrust) with the positioning system mounted on it. The recorded quadcopter noise had a broadband noise compared to the SSSound. Taking these SSSound properties into account, the noise tolerance of the SSSLPS was improved, achieving a positioning accuracy of 23.2 mm and 31.6 mm accuracy within 12 × 6 m for both Time-division Multiple Access (TDMA) and Frequency-division Multiple Access (FDMA) modulation. The results demonstrate that the SSSLPS is an accurate, robust positioning system that is noise tolerant and can used for quadcopter operation even within a small greenhouse.

Sound-based positioning systems are a potential alternative low-cost navigation system. Recently, we developed such an audible sound-based positioning system, based on a spread spectrum approach. It was shown to accurately localize a stationary object. Here, we extend this localization to a moving object by compensating for the Doppler shift associated with the object movement. Numerical simulations and experiments indicate that by compensating for the Doppler shift, the system can accurately determine the position of an object moving along a non-linear path. When the object moved in a circular path with an angular velocity of 0 to 1.3 rad/s, it could be localized to within 25 mm of the actual position. Experiments also showed the proposed system has a high noise tolerance of up to −25 dB signal-to-noise ratio (SNR) without compromising accuracy.