#AutomaticTargetRecognition #AutomaticGaitRecognition

Defence R&D Canada http://www.dtic.mil/dtic/tr/fulltext/u2/a427483.pdf (p15-16)

When the radar transmits an electromagnetic signal to a target, the signal interacts with the target and then returns to the radar. The change in the properties of the returned signal reflects on the characteristics of the target.

When the target is moving, the carrier frequency of the returned signal will be shifted due to Doppler effect. The Doppler frequency shift can be used to determine the radial velocity of the moving target. If the target or any structure on the target is vibrating or rotating in addition to target translation, it will induce frequency modulation on the returned signal that generates sidebands about the target's Doppler frequency. This modulation is called the microDoppler (m-D) phenomenon.

The m-D phenomenon can be regarded as a characteristic of the interaction between the vibrating or rotating structures and the target body. If the target undergoes a vibration or rotation, then the Doppler frequency shift generated by the vibration or rotation is a time-varying function and imposes aperiodic time-varying modulation onto the carrier frequency.

The modulation contains harmonic frequencies that depend on the carrier frequency, the vibration or rotation rate, and the angle between the direction of vibration and the direction of the incidentwave. While the Doppler frequency induced by the target body is constant, the m-D due to a vibrating or rotating structure of the target is a function of dwell time.

The micro-Doppler effect was originally introduced in laser systems, but it can also be observed in microwave radar systems. The fundamental research of the m-D phenomenon in radar is a relatively unexplored and untested area [5]. Micro-Doppler radar signatures of battlefield engine are caused by vibration. In many cases, a target or any structure on the target may have vibrations or rotations that are referred to as micro-motion dynamics. For example, vibrations generated by a vehicle engine may be detected from the surface vibration of the vehicle.

From the m-D signature of engine vibration signals, one can further distinguish a gas turbine engine of a tank from a diesel engine of a bus. Vehicles produce their own types of m-D signature as do helicopters. Therefore, the m-D effect can be used to identify specific types of battlefield targets and determine their movement and engine speed.

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Obtaining radar signatures of personnel is another important application of m-D. The human walking gait is a complex motion behaviour that comprises different movements of individual body parts. Since September 11, Automatic Gait Recognition (AGR) technology is growing in significance. Because gait recognition technology is so new, researchers are assessing its uniqueness and methods by which it can be evaluated. Various computer vision and ultrasound techniques have been developed to measure gait parameters [26-29]. Real-Time AGR radar systems have recently been recognized as advantageous solutions for detecting, classifying and identifying human targets at distances in all light and weather conditions. Radar has certain advantages over electrooptical (EO) systems and video cameras in that it can penetrate into clothes, does not require light, and operates in fog and other low-visibility weather conditions. However, radar-based recognition is such a novel approach that much fundamental research has yet to be done in this area. The radar sends out a signal and then measures the echo that contains rich information about the various parts of the moving body.

There are different shifts for different body parts, because they are moving at different velocities. For example, a walking man with swinging arms may induce frequency modulation of the returned signal and generate sidebands about the body Doppler.

Classification of micro-Doppler signatures of human motions using log-Gabor filters

http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7348901