This paper addresses the problem of target motion analysis using underwater sound pressure levels acquired by sonar operating in passive mode. Traditionally, this task is performed using bearing information, and various filtering algorithms, particularly particle filter methods, have shown strong performance in this domain. To improve upon existing approaches, this paper proposes combining bearing information with received noise levels. This approach offers the advantage of avoiding additional sensors compared to bearings-only tracking, as sound pressure levels can be measured with hydrophones, and underwater transmission losses estimated through computational simulations based on commonly available environmental data. The effectiveness of this method, compared to bearings-only tracking, is illustrated using simulated data, showing improved performance even in the absence of observer maneuvers for this challenging nonlinear, multimodal tracking problem.