Abstract: A measure of target's angular spread is introduced,which is defined as Angular Distribution Index(ADI).A target echo filtering method is developed based on different ADIs of target,reverberation and noises in active sonar.The ADI is computed from the observation data vector formed by a compact bank of receiving beams which are overlapped in receiving azimuth domain.Properties of ADI under different conditions of SNR,angular spread of target,reverberation and noise sources are analyzed in the formation of Monte Carlo Integration.According to the properties of ADI,the target can be separated from reverberation and noise if an appropriate threshold of ADI is adopted.This method does not require neither the independence of reverberation with echo nor the independence between reverberation/noise sources. And therefore it is advantageous over conventional processors for active sonar where reverberation is always hard to deal with due to its correlation with echo and distribution in space.It is also true for noise-limited target detection which may suffer from much higher noise level due to the beam sidelobe leakage,wide beam receiving and sonar platform maneuvering unless the proposed target echo filtering is applied.Using experimental data from Autonomous Underwater Vehicle(AUV),it is shown the proposed method can suppress the reverberation and flow noise effectively.As a result, the SNR of target detection can be significantly improved.