Michael C. Wicks

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In order to improve upon automated sensor performance for security applications in public and private settings, numerous alternative sensor designs have been developed to provide affordable and effective detection and identification performance. Radio frequency (RF) sensors offer a balanced approach to system design for a wide variety of geome-tries and(More)
In the situation that a radar platform is moving very fast, the number of training data used in space-time adaptive processing (STAP) is a major concern. Less number of training data is preferred in this situation. In this paper, four versions of statistical-based and direct data domain STAPs are discussed and compared their performance when the number of(More)
This paper addresses the issue of spatial diversity in radar applications. Typically, information concerning ground and air targets is obtained via monostatic radar. Increased information is often equated with increased bandwidth in these radar systems. However, geometric diversity obtained through multistatic radar operations also affords the user the(More)
—A direct data domain (D 3) least-squares space–time adaptive processing (STAP) approach is presented for adap-tively enhancing signals in a nonhomogeneous environment. The nonhomogeneous environment may consist of nonstationary clutter and could include blinking jammers. The D 3 approach is applied to data collected by an antenna array utilizing space and(More)
—Radio frequency (RF) tomography is proposed to detect underground voids, such as tunnels or caches, over relatively wide areas of regard. The RF tomography approach requires a set of low-cost transmitters and receivers arbitrarily deployed on the surface of the ground or slightly buried. Using the principles of inverse scattering and diffraction(More)
—This is the second paper in a series on a new initiative of wireless tomography. The goal is to combine two areas: wireless communication and radio tomography. This paper studies wireless tomography from a system engineering's point of view. Machine learning and waveform diversity will be applied to wireless tomography. The potential system architecture(More)
A direct data domain deterministic approach utilizing a nonuniform array to adaptively estimate the signal strength of an incoming signal in the presence of strong jammers, clutter, and thermal noise is presented. This method is based on choosing a weighted difference of neighboring antenna outputs, based on the direction of arrival of the signal of(More)
—Spectrum sensing is a fundamental problem in cognitive radio. We propose a function of covariance matrix based detection algorithm for spectrum sensing in cognitive radio network. Monotonically increasing property of function of matrix involving trace operation is utilized as the cornerstone for this algorithm. The advantage of proposed algorithm is it(More)