<p>The micro-Doppler signature of a target exhibiting micro-motions can be utilized to classify and obtain detailed information about its structure. This signature is typically extracted using time-frequency transforms of the received radar signal. In cases where the target is a helicopter or drone with rotating blades, appropriate processing can reveal characteristics such as blade length, rotation frequency, and the number of blades, which are necessary in determining the type of aircraft. However, time-frequency analysis and subsequent image processing impose significant computational burdens and require substantial memory. To estimate the three unknown parameters of the rotating blades, we need to solve three equations. In this article, we propose a low-complexity method that eliminates the time-frequency transform phase for parameter estimation of rotating blade targets. Our approach utilizes the real and imaginary components of the received signal separately to estimate all unknown parameters. Computer simulations and experimental results are presented to demonstrate the effectiveness of the proposed method.</p>