Abstract
Nonlinear radar exploits the difference in frequency between radar waves that illuminate and are reflected from electromagnetically nonlinear targets. Harmonic radar is a special type of nonlinear radar that transmits one or multiple frequencies and listens for frequencies at or near their harmonics. Nonlinear radar differs from traditional linear radar by offering high clutter rejection and is particularly suited to the detection of devices containing metals and semiconductors. Examples include tags for tracking insects, tags worn by humans for avoiding collisions with vehicles, or for monitoring vital signs. Such tags contain a radio-frequency (RF) nonlinearity, often a Schottky diode, connected to a suitable antenna. Targets with inherent nonlinearities, such as metal contacts, semiconductors, transmission lines, antennas, filters, and ferroelectrics, also respond to nonlinear radar. In this paper, the successful exploitation of harmonic radar for moving target imaging and synthetic aperture imaging of targets, while suppressing clutter signals from linear targets, are presented. Our results demonstrate some unique advantages of harmonic radar over its traditional linear counterpart.
Highlights
IntroductionOne of the earliest observations of nonlinearities in electrical circuits was made by Michael
One of the earliest observations of nonlinearities in electrical circuits was made by MichaelFaraday in 1833 [1]
We present the basic principles of harmonic radar, and provide experimental evidence of its ability to suppress linear clutter, perform detection and indication of slow moving nonlinear targets, and perform high resolution synthetic aperture imaging
Summary
One of the earliest observations of nonlinearities in electrical circuits was made by Michael. Faraday in 1833 [1]. He observed that the resistance of particular resistors changed as a function of temperature. The modern day realization of this effect is the thermistor. A system is considered linear if it satisfies two properties, namely, homogeneity and additivity. A system is homogeneous if scaling the input to the system results in a scaled version of the output. A system is additive if, when multiple inputs are summed, the result is the sum of the outputs. Systems that do not meet both of these conditions are considered to be nonlinear systems.
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