There has been a plethora of papers dealing with wireless communication that use techniques, which when viewed from the perspective of a Maxwellian framework raise more questions than they answer. By Maxwellian framework we imply not only the relevance of electromagnetics in studying communication systems but also the proper interpretation of an ensemble processing in mathematical physics which was first introduced by Maxwell to study the behavior of an aggregate of molecules rather than the property of individuals. Initially, most of the modern signal processing techniques was developed for scalar acoustic problems. However, with the advent of wireless, these same techniques are being applied to the vector electromagnetics problem, which is fundamentally different in concept with respect to the scalar acoustic problem. The objective is to discuss some of these concerns associated with some of the current modeling methodologies particularly related to propagation modeling and antenna diversity. A goal is to initiate a dialog about the scientific merits of these new applications. One of the points to be made is that an incorrect use of probability theory can often lead to erroneous conclusions that directly contradict the principles of physics.A few examples are presented to initiate this dialog, mainly the applicability of scalar techniques to the vector wireless problem, including a proper interpretation of the Shannon channel capacity theorem. A methodology is also presented to illustrate how a simple multiple-input-multiple-output system can be based on the principles of reciprocity. Integration of the electromagnetic principles in some of the current methodologies of signal processing and communications theory may lead to a better system.

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In this paper, a technique that can automatically detect and classify objects buried under the ground is proposed. The technique employs a ground‐penetrating radar that transmits electromagnetic waves in order to strike the objects and then receives the backscattering electromagnetic wave to perform signal processing. This signal processing is divided into four main steps as follows. First, preprocessing is used to reduce the clutter due to the effect of the media layer interface. Second, the late time of the scattering signal is estimated using a simple cross correlation. Third, a few successive poles are extracted from the scattering response at the estimated late time by using the short‐time matrix pencil method. Finally, the extracted poles are fed for object classification with different constitutions and/or shapes using a support vector machine. Simulations according to the practical situation in three southern provinces of Thailand to counter the improvised explosive devices were set up. The performance of the proposed technique was evaluated. The simulation results showed that the proposed technique can efficiently detect and classify buried objects for counter‐improvised explosive device operations in the military.