Space time adaptive processing (STAP) in multi input multi output (MIMO) radar

Radar is a system that uses electromagnetic waves to detect, locate and measure the speed of reflecting objects such as aircraft, ships, spacecraft, vehicles, people, weather formations, and terrain. It transmits the electromagnetic waves into space and receives the echo signal reflected from objects. By applying signal processing algorithms on the reflected waveform, the reflecting objects can be detected. Furthermore, the location and the speed of the objects can also be estimated. Early radar development was mostly driven by military and military is still the dominant user and developer of radar technology. Military applications include surveillance, navigation, and weapon guidance. However, radar now has a broader range of applications including meteorological detection of precipitation, measuring ocean surface waves, air traffic control, police detection of speeding traffic, sports radar speed guns, and preventing car or ship collisions. The original contribution of this thesis is a multiple-input multiple-output (MIMO) generalization of space-time adaptive processing (STAP) to mitigate spread doppler clutter returns in radar. Multi input multi output (MIMO) radar is a radar system with multiple receive and transmit antennas, that can transmit independent waveforms on each transmit elements. Although many traditional multi-antenna radar concepts such as phased- array, receive beamforming, synthetic aperture radar (SAR), polarimetry and interferometry can be seen as special cases of MIMO radar, the distinct advantage of a multi-antenna radar system with independent transmit waveforms is the increased number of degrees of freedom leading to improved resolution and performance in detection and parameter estimation tasks. MIMO radar possesses significant potentials for fading mitigation, resolution enhancement, and interference and jamming suppression. Fully exploiting these potentials can result in significantly improved target detection, parameter estimation, target tracking and recognition performance. The MIMO radar technology has rapidly drawn considerable attention from many researchers. Several advantages of MIMO radar have been discovered by many different researchers such as increased diversity of the target information, excellent interference rejection capability, improved parameter identifiability, and enhanced flexibility for transmit beampattern design. The degrees of freedom introduced by MIMO radar improves the performance of the radar systems in many different aspects. However, it also generates some issues. It increases the number of dimensions of the received signals. Consequently, this increases the complexity of the receiver. Furthermore, the MIMO radar transmits an incoherent waveform on each of the transmitting antennas. This in general reduces the processing gain compared to the phased array radar. The multiple arbitrary waveforms also affects the range and Doppler resolution of the radar system. A promising application of MIMO radar is the identification of slowly moving targets using airborne MIMO radar platforms. The advantage of using MIMO in this configuration is its ability to synthesize a larger virtual array with relatively fewer antennas. This allows higher spatial resolution and better separation of returns from ground clutter and targets. The space-time adaptive processing (STAP) methods originally developed for Single-input, Multiple-output (SIMO) radar are applicable to MIMO radar systems after proper pre-processing of the received signals. The performance of STAP algorithm critically hinges on the structure of the clutter covariance matrix; therefore, MIMO STAP methods will benefit greatly from theoretical and empirical study of the clutter statistics. Of particular interest is clutter subject to multipath propagation between transmit and receive arrays. Significant of multipath clutter can occure in over-the-horizon (OTH) radar data when ground or ocean surface returns undergo multiple ionospheric scattering that couse considerable doppler frequency and wavenumber spreads. In such situation, conventional single-input multi-output (SIMO) STAP cannot mitigate doppler spread mainlobe clutter without suppressing the target in conjunction. With a slight modification, STAP methods developed originally for the single-input multiple-output (SIMO) radar (phased array radar) can also be used in MIMO radar. However, in the MIMO radar, the rank of the jammer-and-clutter subspace becomes very large, especially the jammer subspace. It affects both the complexity and the convergence of the STAP algorithm. After reconsidering the advantages and drawbacks of the extended MIMO-STAP, namely the sample matrix inversion (SMI) and eigencanceller (EC), fast approximated power iteration (FAPI) algorithms, we propose fast and stable YAST algorithm the range recursive algorithm as an alternative to resolve the convergence and complexity problems. The novelty in the YAST algorithm was the lower computational cost (linear if the data correlation matrix satisfies a so-called shift-invariance property), and the extension to minor subspace tracking. However, the original implementation of the YAST algorithm suffered from a numerical stability problem (the subspace weighting matrix slowly loses its orthonormality). We thus used in this thesis a new implementation of YAST, whose stability is established theoretically and tested via numerical simulations. This algorithm combines all the desired properties for a subspace tracker: remarkably high convergence rate, lowest steady state error, linear complexity, and numerical stability regarding the orthonormality of the subspace weighting matrix. The contribution of this work can be summarized in four parts. First, we present the basic review of the detection and ranging in radar system. Multistatic Radar Systems are examined, and Phased Array Radars are covered to give the reader the opportunity to compare those systems with MIMO Radar. Second, we fully explain the concept of coherent MIMO radar and its difference with SIMO or phased array radar, signal model and improvements that coherent MIMO radar systems offer like high resolution and parameter identifiability. In the third part we briefly explain space-time adaptive processing (STAP) in MIMO radar. Then we discuss about different algorithms of STAP in MIMO radar as if sample matrix inversion (SMI), eigencanceller (EC), fast approximated power iteration (FAPI) and fast and stable YAST. Ultimately results of the simulations which have been performed in this thesis study are introduced and simulations are performed to present STAP performance of different MIMO radar configurations.