Title :
A Lower Bound for Sequential Estimators
Author :
Bouleux, Guillaume ; Boyer, Rémy
Author_Institution :
Univ. Jean Monnet, St. Etienne
Abstract :
A popular class of parameter estimation method is based on a sequential/iterative scheme. In this framework, each component is estimated one by one and at each iteration the underlying model is based on the estimation of a single component corrupted by a structured interference (the other components) and by an unstructured Gaussian noise. So, in the context of the bearing estimation problem, we derive the deterministic Cramer-Rao Bound, called Interfering CRB (I-CRB), associated with this model. In particular, we show that for low Interference to Noise Ratio (INR), the I-CRB reaches the CRB for a single component (without structured interference). Inversely, for high INR, the I-CRB is equal to the Prior-CRB where we assume the exact knowledge of the structured interference. In addition, we show that in the closely-spaced bearings, the I-CRB has two typical regimes depending of the INR.
Keywords :
Gaussian noise; interference (signal); iterative methods; parameter estimation; sequential estimation; signal processing; Cramer-Rao bound; bearing estimation problem; closely-spaced bearings; interference to noise ratio; iterative scheme; parameter estimation method; sequential estimators; sequential scheme; unstructured Gaussian noise; Context modeling; Direction of arrival estimation; Gaussian noise; Interference; Iterative methods; Parameter estimation; Radar signal processing; Signal analysis; Signal processing algorithms; Signal to noise ratio;
Conference_Titel :
Computational Advances in Multi-Sensor Adaptive Processing, 2007. CAMPSAP 2007. 2nd IEEE International Workshop on
Conference_Location :
St. Thomas, VI
Print_ISBN :
978-1-4244-1713-1
Electronic_ISBN :
978-1-4244-1714-8
DOI :
10.1109/CAMSAP.2007.4498019