Extended quality identifiers for radar measurements

Abstract

Synthetic aperture radar and ordinary radar systems must be optimized with respect to some quality criteria. A commonly used optimization gives minimum mean-square variance error. However, this optimization cannot take into account all characteristics of the radar image, such as speckle. This leads to a number of non-optimal secondary processing algorithms (nonlinear filtering, statistical estimation, etc.). The paper presents common quality criteria applicable to space and space-time processing. Radar image formation errors are separated into three kinds: dynamic, fluctuation and noise errors. Dynamic errors are caused by smoothing the radar space ambiguity function. One realisation of the stochastic process observed during the finite time interval leads to inconsistent estimation, which is called fluctuation error (speckle noise). Noise error is caused by additional noise present in the input. The paper proposes statistical criteria applicable to optimizing the processing algorithms in radar systems.