26-04-2011, 12:43 PM
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Chapter 1
INTRODUCTION
Recently, the concept of multiple-input multiple-output (MIMO) radars has drawn considerable attention. MIMO radars emit orthogonal waveforms or non coherent waveforms instead of transmitting coherent waveforms which form a focused beam in traditional transmitter based beam forming. In the MIMO radar receiver, a matched filter bank is used to extract the orthogonal waveform components. There are two different kinds of approaches for using the non coherent waveforms. First, increased spatial diversity can be obtained.
In this scenario, the transmitting antenna elements are far enough from each other compared to the distance from the target. Therefore the target radar cross sections (RCS) are independent random variables for different transmitting paths. When the orthogonal components are transmitted from different antennas, each orthogonal waveform will carry independent information about the target. This spatial diversity can be utilized to perform better detection. Second, a better spatial resolution for clutter can be obtained. In this scenario, the distances between transmitting antennas are small enough compared to the distance between the target and the radar station. Therefore the target RCS is identical for all transmitting paths.
The phase differences caused by different transmitting antennas along with the phase differences caused by different receiving antennas can form a new virtual array steering vector. With judiciously designed antenna positions, one can create a very long array steering vector with a small number of antennas. Thus the spatial resolution for clutter can be dramatically increased at a small cost.
The adaptive techniques for processing the data from air-borne antenna arrays are called space-time adaptive processing (STAP) techniques. The basic theory of STAP for the traditional single-input multiple-output (SIMO) radar has been well developed. There have been many algorithms proposed in and the references therein for improving the complexity and convergence of the STAP in the SIMO radar. With a slight modification, these methods can also be applied to the MIMO radar case. The MIMO extension of STAP can be found in The MIMO radar STAP for multipath clutter mitigation can be found in .However, in the MIMO radar, the space-time adaptive processing (STAP) becomes even more challenging because of the extra dimension created by the orthogonal waveforms. On one hand, the extra dimension increases the rank of the jammer and clutter subspace, especially the jammer subspace. This makes the STAP more complex. On the other hand, the extra degrees of freedom created by the MIMO radar allow us to filter out more clutter subspace with little effect on SINR.
Using the geometry of the MIMO radar and the prolate spheroidal wave function (PSWF), a method for computing the clutter subspace is developed. Then we develop a STAP algorithm which computes the clutter subspace using the geometry of the problem rather than data and utilizes the block-diagonal structure of the jammer covariance matrix. Because of fully utilizing the geometry and the structure of the covariance matrix, our method has very good SINR performance and significantly lower computational complexity compared to fully adaptive methods.
In practice, the clutter subspace might change because of effects such as the internal clutter motion (ICM), velocity misalignment, array manifold mismatch, and channel mismatch. In this, we consider an “ideal model”, which does not take these effects into account. When this model is not valid, the performance of the algorithm will degrade. One way to overcome this might be to estimate the clutter subspace by using a combination of both the assumed geometry and the received data. Another way might be to develop a more robust algorithm against the clutter subspace mismatch. These ideas will be explored in the future.
1.1 Review of the MIMO Radar
In this section, the MIMO radar idea is reviewed in brief. The focus will be on using MIMO radar to increase the degrees of free-dom. Figure 1.1 illustrates a MIMO radar system. The transmitting antennas emit orthogonal waveforms φk (τ ). At each receiving antenna, these orthogonal waveforms can be extracted by M matched filters, where M is the number of transmitting antennas. Therefore there are a total of N M extracted signals, where N is the number of receiving antennas. The signals reflected by the target at direction θ can be expressed
