Abstract: ‍ ‍In this paper， we tries to apply the concept of energy matching in the matched field processing to the optimization of the array beamforming to solve the weak signal detection problem of passive sonar. First， the detection capabilities based on four matched-field processors： linear incoherent， MVDR incoherent， linear coherent and MVDR coherent， are compared， then the output signal-to-noise ratio （SNR） and output signal power of linear incoherent processor are analyzed. Based on the analysis， the detection ability of the linear incoherent processor will decrease when the frequency fluctuation of the sound source increases. In order to obtain a higher output signal-to-noise ratio， this paper proposes a maximum SNR processor， which can achieve the highest output SNR in the processing bandwidth under ideal conditions. The maximum SNR processor does not eliminate the influence of the sound source through normalization， but uses the estimated value of the sound source spectrum and the copy field to directly match the received data. This paper proves that the detection ability of the maximum SNR processor is better than that of the linear incoherent processor， and this conclusion is further verified by simulation experiments.