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Tracking performance prediction and evaluation: the modified Riccati equation
 

Summary: Tracking performance prediction and evaluation: the
modified Riccati equation
Yvo Boers and Hans Driessen
THALES NEDERLAND
Haaksbergerstraat 49
7554 PA Hengelo
The Netherlands
ABSTRACT
In this paper, some recent results on the modified Riccati equation are studied. This modified Riccati equation
has already been associated with tracking a target under measurement uncertainty. We consider the special
case of tracking a target without clutter, but with a probability of detection of less than one. This special case
has received quite some attention recently, especially in relationship with Cramer Rao bounds, or equivalently
expected performance. Furthermore, in some other recent works, new theoretical results on the modified Riccati
equation have been derived. We will compare these results and point out their importance for performance
assessment and prediction in a target tracking context.
Keywords: Target Tracking, Riccati equation, Kalman Filter, Cramer Rao bounds
1. INTRODUCTION
In this paper the modified Riccati equation, as it was originally formulated in1
is revisited. This modified Riccati
equation plays a role in several target tracking related topics, such as: Cramer Rao Lower Bounds (CRLB's),

  

Source: Al Hanbali, Ahmad - Department of Applied Mathematics, Universiteit Twente

 

Collections: Engineering