In this paper, radar is discussed in the context of a multiple-input multiple-output (MIMO) system model. A comparison is made between MIMO wireless communication and MIMO radar. Examples are given showing that many traditional radar approaches can be interpreted within a MIMO context. Furthermore, exploiting this MIMO perspective, useful extensions to traditional radar can be constructed. Performance advantages in terms of degrees of freedom and resolution are discussed. Finally, a MlMO extension to space-time adaptive processing (STAP) is introduced as applied to ground moving-target indication (GMTI).

Multiple-input multiple-output (MIMO) radar and imaging: degrees of freedom and resolution

This paper addresses the problem of radar waveform design for target identification and classification. Both the ordinary radar with a single transmitter and receiver and the recently proposed multiple-input multiple-output (MIMO) radar are considered. A random target impulse response is used to model the scattering characteristics of the extended (nonpoint) target, and two radar waveform design problems with constraints on waveform power have been investigated. The first one is to design waveforms that maximize the conditional mutual information (MI) between the random target impulse response and the reflected waveforms given the knowledge of transmitted waveforms. The second one is to find transmitted waveforms that minimize the mean-square error (MSE) in estimating the target impulse response. Our analysis indicates that under the same total power constraint, these two criteria lead to the same solution for a matrix which specifies the essential part of the optimum waveform design. The solution employs water-filling to allocate the limited power appropriately. We also present an asymptotic formulation which requires less knowledge of the statistical model of the target

http://www.ece.lehigh.edu/SPCRL/PAPERS/TAES-07.pdf

MIMO radar waveform design based on mutual information and minimum mean-square error estimation

The radio-frequency (RF) electromagnetic spectrum, extending from below 1 MHz to above 100 GHz, represents a precious resource. It is used for a wide range of purposes, including communications, radio and television broadcasting, radionavigation, and sensing. Radar represents a fundamentally important use of the electromagnetic (EM) spectrum, in applications which include air traffic control, geophysical monitoring of Earth resources from space, automotive safety, severe weather tracking, and surveillance for defense and security. Nearly all services have a need for greater bandwidth, which means that there will be ever-greater competition for this finite resource. The paper explains the nature of the spectrum congestion problem from a radar perspective, and describes a number of possible approaches to its solution both from technical and regulatory points of view. These include improved transmitter spectral purity, passive radar, and intelligent, cognitive approaches that dynamically optimize spectrum use.

/pdf/radar-spectrum-engineering-and-management-technical-and-1akd12nvp3.pdf

Radar Spectrum Engineering and Management: Technical and Regulatory Issues

dix A. Even if you don’t choose to memorize them this system aids in reference and retreival of important formulas. The book was compiled from notes developed during eight years of teaching a graduate course on the subject and was used as a text. Thus it has been student tested. Appendix F contains a number of problems, grouped to be used on a chapter by chapter basis The problems are designed to illustrate practical applications of the text material. The parts of this book of most interest and value to the EMC engineer will be the chapters on Thermal Noise, Antennas, Propagation and Transmission Lines, and  Reflection and Refraction. This is not  to downpade the chapters on Statistics and Its Applications, Signal Processing and Detection, and Some System Characteristics which also contain much potentially useful materials. Additional plus values for the book include a list of 40 references, a table of symbols used throughout the book, and a subject index. Some readers may find the condensed type and close line spacing hard to read. It was apparently set up by typewriter using an elite type face with single line spacing. When reduced down to a 6 by 9 5 inch size page it is too crowded for easy reading. In spite of this shortcoming your reviewer recommends this book as a worthwhile reference in this field of interest.

http://ieeexplore.ieee.org/iel5/5/31269/01455368.pdf

Signal analysis

A confluence of recent breakthroughs in knowledge-aided (KA) processing and adaptive transmit (ATx) radar technologies has enabled a new generation of cognitive radar architectures that affords unprecedented levels of intelligent adaptivity. In this paper one such architecture is introduced by the integration of KA and ATx methods to produce a new cognitive radar that encompasses an environmental dynamic database (EDDB), a “look-ahead” high performance embedded computing (HPEC) architecture pioneered under the DARPA/AFRL KASSPER project, and adaptive transmit (spatio-temporal) functionality.

Cognitive Radar: The Knowledge-aided Fully Adaptive Approach

Optimal detection of a target return contaminated by signal-dependent interference, as well as additive channel noise, requires the design of a transmit pulse f(t) and a receiver impulse response h(t) jointly maximizing the output signal to interference plus noise ratio (SINR). Despite the highly nonlinear nature of this problem, it has been possible to show that f(t) may always be chosen minimum-phase. A full analysis concludes with the construction of an effective numerical procedure for the determination of optimal pairs (f,h) that appears to converge satisfactorily for most values of input SINR. Extensive simulation reveals that the shape of f(t) can be a critical factor. In particular, the performance of a chirp-like pulse is often unacceptable, especially when clutter and channel noise are low-pass dominant and comparable.

Optimal transmit-receiver design in the presence of signal-dependent interference and channel noise

Theory and Design of Maximally Flat Low-Pass, High-Pass Reactance-Ladder Diplexers

Coupling networks that divide the frequency spectrum into separate frequency bands and also provide desired filtering are known as multiplexers. In this paper we present four new theorems concerning the synthesis-theoretic structure of lumped passive multiplexers constructed as lossless reciprocal n-ports. In particular we prove in Theorem 1 that any set of n – 1 admissible power gains, complementary or otherwise, can be realized by a series interconnection of n–1 appropriately chosen non-Foster positive-real functions. In Theorems 2–4 we establish various necessary and sufficient conditions for the realization of bounded-real gains s21(p),…, sn1(p) given both in magnitude and phase. These conditions reveal that the general problem is one of Nevalinna-Pick interpolation. Lastly, five worked examples are used to illustrate all facets of the theory.

New theorems in the synthesis of passive multiplexers

In an excellent paper written in 1983 Van Hove et al. [ IEEE Trans. Acoust. Speech Signal Process.ASSP-31, 1286 ( 1983)] proved that a real polynomial P(z), free of zeros in |z| = 1, is determined uniquely by its magnitude A(θ) and the sign of its real part u(θ) for z = ejθ. Van Hove et al. also indicated a possible extension to real polynomials in more than one variable and suggested an iterative procedure for the recovery of P(z). The restriction to polynomials (or rational functions), real or otherwise, is not crucial. In fact, on due reflection, it is seen that the problem continues to make sense for functions H(z) = H(z1, z2, …, zn) in n variables that are holomorphic in the open polydisc Un = {z:|z1| < 1, |z2| < 1, …, |zn| < 1}, continuous in the closure Ūn = {z:|z1| ≤ 1, |z2| ≤ 1, …, |zn| ≤ 1}, and free of zeros on its distinguished boundary Tn = {z:|z1| = 1, |z2| = 1, …, |zn| = 1}. The collection A(Un) of functions holomorphic in Un and continuous in Ūn is Rudin’s polydisc algebra [ W.\n Rudin\n \n , Function Theory in Polydiscs ( Benjamin, NewYork, 1969)]. Our main result can be stated as follows. Let H(z) belong to A(Un) and be free of zeros in Tn. For real θ = (θ1, θ2, …, θn), write, in terms of real and imaginary parts, H(exp(jθ1), exp(jθ2), …, exp(jθn)) = H(ejθ) = u(θ) + jv(θ), and let A(θ) = |H(ejθ)|; then H(z) is determined uniquely by the functions A(θ) and sign u(θ), together with its value at one point z0 exp(jθ0) ∈ Tn for which u(θ0) ≠ 0. We also clarify the meaning and the scope of this theorem by the use of specific examples, but reconstruction techniques are not discussed.

Dante C. Youla

Papers

Optimal transmit-receiver design in the presence of signal-dependent interference and channel noise

Theory and Design of Maximally Flat Low-Pass, High-Pass Reactance-Ladder Diplexers

New theorems in the synthesis of passive multiplexers

A uniqueness characterization in terms of signed-magnitude for functions in the polydisc algebra

Matched Transmit-Receiver Design in Presence of Signal Dependent Interference