Abstract

This letter explores the possibilities of detecting a moving target and localizing clutter using nonstationary Doppler radar. The detection of a moving target, particularly a human, has many potential applications in the fields of surveillance and rescue. In dangerous environments, Doppler radar can be used to effectively collect information about the surroundings, even through walls. However, a moving platform makes the detection of a moving target complicated due to Doppler shift caused by the clutter. We analyze the pattern of the Doppler shift due to clutter over time and develop a linear regression model that describes this pattern. The location of clutter can be estimated by the model with the time history of the measured Doppler shifts. Although the pattern from clutter follows the mathematical model, the pattern from a moving target does not, resulting in a high-percentage root-mean-square (RMS) fitting error. On the basis of the percentage RMS fitting error, a moving target is differentiated from clutter.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call