Mitre Corporation

About: Mitre Corporation is a company organization based out in Bedford, Massachusetts, United States. It is known for research contribution in the topics: Air traffic control & National Airspace System. The organization has 4884 authors who have published 6053 publications receiving 124808 citations. The organization is also known as: Mitre & MITRE.

Processing and evaluation of multichannel airborne radar measurements (MCARM) measured data

Abstract: Rome Laboratory's (RLs) Multichannel Airborne Radar Measurements (MCARM) program has collected clutter and target data employing an L-band airborne phased array radar testbed. The data collection is at the output of an electronically steered active array mounted on BAC1-11 aircraft. The MCARM array has 16 columns, each consisting of two four-element subarrays. Each subarray has its own output or is combined into a single output per column with up to 24 outputs for the array. Space-time adaptive processing (STAP) techniques simultaneously combine the signals from the elements of an array antenna and pulses of a radar waveform to suppress interference and provide target detection. To obtain adequate clutter power with the limited power-aperture product of the array for STAP analysis, the transmit mainlobe power can be focused in the receive beam sidelobe region or the transmit beam can be spoiled for broader angular coverage. In addition, the data is collected at different platform altitudes and radar waveforms over different terrain. The performance improvement achievable against Doppler-spread clutter that can be achieved with STAP using the L-band data is demonstrated. We present processing results of representative MCARM data files to demonstrate that the adaptive processing can help to detect targets in a nonhomogeneous environment. The limitations of the number of independent clutter samples in estimating the covariance matrix and its impact on target cancellation are examined by processing files with real and synthetic targets.

Synthesis of adaptive monopulse patterns

Abstract: A procedure is developed to simultaneously synthesize sum and difference patterns for space-time adaptive processing (STAP) in such a way that a specified monopulse slope after adaptation is achieved.

On the wavelet transform of fractional Brownian motion

Abstract: A theorem characterizing fractional Brownian motion by the covariance structure of its wavelet transform is established. The authors examine whether there are alternate Gaussian processes whose wavelet transforms have a natural covariance structure. In addition, the authors examine if there are any Gaussian processes whose wavelet transform is stationary with respect to the affine group (i.e. the statistics of the wavelet transform do not depend on translations and dilations of the process). >

Discrete time queues with phase dependent arrivals

Abstract: The queueing behavior of many communication systems is well modeled by a queueing system in which time is slotted, and the number of entities that arrive during a slot is dependent upon the state of a discrete time, discrete state Markov chain. Techniques for analyzing such systems have appeared in the literature from time to time, but distributions have been presented in only rare instances In the paper, the authors present the probability generating function (PGF) for joint and marginal buffer occupancy distributions of statistical time division multiplexing systems in this class. They discuss inversion of the PGF using discrete Fourier transforms, and also discuss a simple technique for obtaining moments of the queue length distribution. Numerical results, including queue length distributions for some special cases, are presented. >

Exact performance of STAP algorithms with mismatched steering and clutter statistics

Abstract: Adaptive algorithms for receivers employing antenna arrays have received significant attention for radar systems applications. In the majority of these algorithms, the covariance matrix for the clutter-plus-noise is characterized by using samples taken from range cells surrounding the test cell. If the underlying covariance matrix of the test cell is different from the average covariance matrix of the surrounding range cells, significant performance degradation may result. Exact expressions for performance are derived for such cases, when any of a set of popular space-time adaptive processing (STAP) algorithms are used. Numerical evaluation of these expressions illustrates how variations in the parameters of these equations affect probability of detection and probability of false alarm. The equations are utilized to determine an upper bound an the performance of this class of STAP algorithms.