This paper investigates the use of adaptive beamforming techniques to increase the performance of a sonar imaging system developed at the Scripps Institution of Oceanography to monitor the migration of zooplankton. The original system, known as Fish Television (FTV), images a volume using an 8 x 8 grid of beams in elevation and azimuth. Imaging currently performed with the FTV system is limited by a 2-deg resolution in both azimuth and elevation. In this paper, both a conventional delay-and-sum beamformer and a minimum variance adaptive beamformer are evaluated for use with the FTV sonar system to increase resolution and reduce sidelobe interference. Through simulation it is shown that by using adaptive beamforming, the image resolution can be improved to 1/2 deg in azimuth and elevation for targets with signal-to-noise ratios of at least 20 dB. Results using acoustic data from the Gulf of Eilat are compared to the original images of the FTV sonar system to illustrate the improvement in resolution, accuracy, and dynamic range achieved by adaptive beamforming.