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2 results on '"Andi Huang"'

1. An Investigation of Rotary Drone HERM Line Spectrum under Manoeuvering Conditions

Author

Peter Klaer, Andi Huang, Pascale Sévigny, Sreeraman Rajan, Shashank Pant, Prakash Patnaik, and Bhashyam Balaji

Subjects
micro-Doppler, UAV, drone, radar, HERM lines, spool lines, Chemical technology, TP1-1185
Abstract

Detecting and identifying drones is of great interest due to the proliferation of highly manoeuverable drones with on-board sensors of increasing sensing capabilities. In this paper, we investigate the use of radars for tackling this problem. In particular, we focus on the problem of detecting rotary drones and distinguishing between single-propeller and multi-propeller drones using a micro-Doppler analysis. Two different radars were used, an ultra wideband (UWB) continuous wave (CW) C-band radar and an automotive frequency modulated continuous wave (FMCW) W-band radar, to collect micro-Doppler signatures of the drones. By taking a closer look at HElicopter Rotor Modulation (HERM) lines, the spool and chopping lines are identified for the first time in the context of drones to determine the number of propeller blades. Furthermore, a new multi-frequency analysis method using HERM lines is developed, which allows the detection of propeller rotation rates (spool and chopping frequencies) of single and multi-propeller drones. Therefore, the presented method is a promising technique to aid in the classification of drones.

Published
2020
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2. Radar Micro-Doppler-based Rotary Drone Detection using Parametric Spectral Estimation Methods

Author

Andi Huang, Sreeraman Rajan, Pascale Sévigny, and Bhashyam Balaji

Subjects
Computer science, 010401 analytical chemistry, Detector, Spectral density estimation, 020206 networking & telecommunications, 02 engineering and technology, 01 natural sciences, Drone, 0104 chemical sciences, law.invention, law, 0202 electrical engineering, electronic engineering, information engineering, Range (statistics), Radar, Akaike information criterion, Spectral resolution, Algorithm, Parametric statistics
Abstract

Micro-Doppler methods of detecting and classifying small UAVs are limited in range due to the weak radar returns from their plastic propellers. Smaller windows of data instead of longer windows are used for detection as stationarity assumptions often fail for longer windows. Traditional non-parametric methods may be inadequate as they have limited spectral resolution with smaller windows and may provide false detection when radar returns are weak. A rotary drone detector using the number of Helicopter Rotation Modulation (HERM) lines is considered in this paper. Two parametric methods for estimating the number of HERM lines, Minimum Description Length (MDL) and Akaike Information Criterion (AIC), are considered for detection purposes. Experiments using real data acquired using a micro-helicopter drone and a commercial ultra-wide band radar reveal that MDL performs significantly better than AIC and the traditional Fourier-based non-parametric estimation methods.

Published
2020
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