The ability of MIMO radar to measure propagation delays from each transmitter to each receiver allows the concept of the sum co-array, reviewed, to be exploited. The sum co-array allows virtual elements to be synthesized and in some cases this can lead to performance advantages. The relationship of the ES matched filter to the sum co-array is discussed in Section 6 and an interesting example of its application to uniform linear arrays (ULAs) is presented. The cross-spectral matrix approach entails the use of ensemble averages which in practical situations are not realizable and furthermore do not capture the statistical aspects and limitations of using noise waveforms. So finally, in Section 7 statistical techniques are used to derive some theoretical limits on the use of noise waveforms resulting from the use of finite sample sizes and some simulations are presented to illustrate these limitations.

Inspec keywords: radar signal processing; matrix algebra; MIMO radar; radar receivers; statistical analysis; matched filters; radar transmitters

Other keywords: ULA; virtual elements; cross-spectral matrix approach; finite sample sizes; noise MIMO radar; noise waveforms; uniform linear arrays; receiver; propagation delay measurement; ES matched filter; sum coarray; statistical techniques; transmitter

Subjects: Filtering methods in signal processing; Other topics in statistics; Radar equipment, systems and applications; Algebra