The pseudo-linear extended Kalman tracking filter previously developed for
passive target tracking using bearings-only measurements required the use o
f a null target state vector as an initial estimate to obtain convergence f
or all types of scenario. The pseudo-linear estimator is projected in such
a way that it does not require any initial estimate at all and at the same
time offers all the features of the extended Kalman filter based pseudo-lin
ear filter; namely sequential processing, flexibility to adopt the variance
of each measurement, etc. The algorithm is tested in Monte Carlo simulatio
ns and its results are presented for two typical scenarios at various noise
levels.