Abstract: The extended Kalman probability hypothesis density (EKPHD) filter has a higher bias in the estimation of the number of targets and a lower estimation accuracy of their states by using the direction cosine coordinate measurements for the phased array radar. To solve this problem, a novel multitarget tracking algorithm called unbiased converted measurements probability hypothesis density (UBCMPHD) filter algorithm is proposed. The proposed algorithm utilizes the unbiased converted method to remain more information about the direction cosine coordinate measurements. Meanwhile, it compensates the bias caused by the converting direction cosine coordinate to Cartesian coordinate measurements, and the means and variances of the converted errors could accurately approximate the firstorder and secondorder moments of Gaussian distribution for original measurements. The simulation results indicate that the proposed algorithm improves the estimation accuracy of both the number of targets and their states.