Controlled acoustic sources have typically been used for imaging the ocean. These sources can either be used to locate objects or characterize the ocean environment. The processing involves signal extraction in the presence of ambient noise, with shipping being a major component of the latter. With the advent of the Automatic Identification System (AIS) which provides accurate locations of all large commercial vessels, these major noise sources can be converted from nuisance to beacons or sources of opportunity for the purpose of studying the ocean. The source localization method presented here is similar to traditional matched field processing, but differs in that libraries of data-derived measured replicas are used in place of modeled replicas. In order to account for differing source spectra between library and target vessels, cross-correlation functions are compared instead of comparing acoustic signals directly. The library of measured cross-correlation function replicas is extrapolated using waveguide invariant theory to fill gaps between ship tracks, fully populating the search grid with estimated replicas allowing for continuous tracking. In addition to source localization, two ocean sensing techniques are discussed in this dissertation. The feasibility of estimating ocean sound speed and temperature structure, using ship noise across a drifting volumetric array of hydrophones suspended beneath buoys, in a shallow water marine environment is investigated. Using the attenuation of acoustic energy along eigenray paths to invert for ocean properties such as temperature, salinity, and pH is also explored. In each of these cases, the theory is developed, tested using numerical simulations, and validated with data from acoustic field experiments.