Communications, Information and Network Security pp 315-331 | Cite as

# Spherically Invariant Random Processes: Theory and Applications

## Abstract

The theory and application of the class of spherically invariant random processes (SIRPs) are reviewed. An SIRP is a random process whose finite-dimensional distributions are scalar functions of quadratic forms in the corresponding sampled variables. Stochastic and system-theoretic properties are discussed, including a basic representation theorem which gives rise to a number of interesting properties concerning the detection, estimation, and interpretation of SIRPs. Applications are reviewed as well, including the use of SIRPs to model speech waveforms, radar clutter returns, and various radio propagation channel disturbances. The use of SIRP modeling in channel equalization and array processing is also described. Finally, some issues concerning the generation and simulation of SIRPs are discussed.

## Keywords

Gaussian Process Array Processing Gaussian Random Process Gaussian Random Vector Atmospheric Noise## Preview

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## References

## Theory

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## SIRP Modeling in Equalization and Array Processing

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