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A dynamic sensor management algorithm based on improved efficacy function is proposed to solve the multi-target and multi-sensory management problem. The tracking task precision requirements (TPR), target priority and sensor use cost were considered to establish the efficacy function by weighted sum the normalized value of the three factors. The dynamic sensor management algorithm was accomplished through control the diversities of the desired covariance matrix (DCM) and the filtering covariance matrix (FCM). The DCM was preassigned in terms of TPR and the FCM was obtained by the centralized sequential Kalman filtering algorithm. The simulation results prove that the proposed method could meet the requirements of desired tracking precision and adjust sensor selection according to target priority and cost of sensor source usage. This makes sensor management scheme more reasonable and effective.