Detection of a target hidden in dense cloud clutter using an echo pattern of pulsed laser radar systems

Abstract

The performance of pulsed laser radar systems has been known to be drastically reduced in dense clutter media, detecting false signals instead of the target. Therefore, high-performance laser radars have become demanding for detection applications. Here, using a multi-scattering Monte Carlo simulation, the pulsed laser radar performance is studied in dense cloud clutter (DCC), involving the role of the clutter extinction coefficient in the cloud return signal waveform of the target. After generating a large number of return signals from the clutter and the target, a unique and prominent feature is found to efficiently distinguish the two signals from each other with a resolution of 0.80 and a minimum signal to clutter ratio of 5.04 dB. A high-pass trapezoidal filter is also designed based on the characteristic feature in order to eliminate the clutter return signal. This proposed filtering method is justified by applying Fourier transform to the return power from the target and cloud, eliminating the clutter frequency response in a low frequency region. Accordingly, it is possible to detect a target hidden in DCC at short distances through receiving an echo pulse pattern.