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Technical report | Radar Detection of Helicopters at low SNR using Time-Frequency Transforms

Abstract

This report describes a radar signal processing technique for detecting helicopter targets based on the micro-Doppler components of the received signal, in a low SNR environment. The Short-Time Fourier Transform (STFT) and the tunable Q-factor wavelet transform were used to identify the micro-Doppler components induced from the rotating main and tail rotor blades of a helicopter radar return. The impact of the STFT parameters on identifying the blade-like components in the reflected signal was investigated. A strong correlation exists between the STFT parameters and the physical properties of the main and tail rotor blades, which can be used to tune the algorithm and improve the detection performance. The algorithms proposed are demonstrated using measured radar data from two different helicopter types.

Executive Summary

This report contains a technique for detecting helicopter targets in radar returns in low signal to noise ratio (SNR) scenarios. In most cases the fuselage return from an airborne target produces the strongest Doppler spectral component, making radar target detection from its body return alone easily achievable. However, this does not provide any additional information regarding the type of target observed. For example, slow moving helicopters can be mistaken for other low speed targets such as ground moving vehicles. By exploiting the micro-Doppler characteristics of the helicopter's radar return caused by its rotating main and tail rotor blades, the detection of the blade-like components in the signal can be used for identifying helicopter targets.

In this work, we take advantage of micro-Doppler characteristics of the target and use the Short-Time Fourier Transform (STFT) to detect rotor blade returns in the received signal. By optimising the STFT parameters, helicopter targets can be detected in returns with a low SNR.

Our proposed algorithm was applied to measured data featuring two helicopter types, namely the Bell 206 and Squirrel AS350. For both helicopter types, the main rotor blades can be detected with a probability of 0.6 at SNR levels as low as -24 dB using a coherent processing interval (CPI) of 150 ms and using the STFT parameters that are matched to the temporal characteristics of the main rotor blade. Once detected, the main blade can be coherently separated from the received signal, and tail rotor blade detection can be subsequently performed. The success of the tail rotor blade detection depends on its SNR level, and the orientation of the helicopter relative to the radar line-of-sight. By using this blade detection process for both main and tail rotors, coarse classification of helicopter targets is possible.

Key information

Author

Duong Duc Nguyen, Si Tran Nguyen Nguyen, Rocco Melino, San-dun Kodituwakku and Hai-Tan Tran

Publication number

DST-Group-TR-3481

Publication type

Technical report

Publish Date

April 2018

Classification

Unclassified - public release

Keywords

Helicopter detection, Short-Time Fourier Transform, Micro-Doppler