The Global Positioning System (GPS) is listed by the US Department of Homeland Security as critical infrastructure. These are essential assets that underpin much of modern society and that, if removed, would have a debilitating impact on our physical health or economic system. This is no exaggeration as GPS timing synchronization is used to coordinate stock exchanges, and as the navigation capabilities it provides are used daily by nearly every smartphone user. Despite GPS being listed as critical infrastructure, it is very easy to interfere with it. Radio frequency interference (RFI) in the form of jamming or spoofing is so incredibly accessible that emitters, made to work with car adapters, capable of incapacitating vehicle tracking exist despite them being illegal. There are several methods for locating RFI emitters, and power difference of arrival (PDOA) is one of the simplest and more raw ways of achieving localization. PDOA is generally used because it requires less data to provide a solution than other alternatives, can be effective against both jamming and spoofing, and works against a variety of RFI signals, such as broadband noise or continuous wave. This paper improves on the PDOA approach by incorporating the saturation of the receivers and the nearest neighboring receivers to adjust the non-linear least squares PDOA solution. Receivers are said to be saturated when their automatic gain control has reached their power floor. This means that if a receiver is saturated it cannot provide an accurate PDOA estimate because there is an infinite amount of locations within a region close to the receiver that the emitter could be located. However, when the nearest neighbors to the saturated receiver are taken into account the saturation helps weight the estimated location. The algorithm presented in this paper is tested using data from a government sanctioned event as part of an educational agreement between CU Boulder and Edwards Air Force Base. The algorithm is tested under both broadband noise and continuous wave RFI signals and proves it can improve PDOA estimation of the emitter location by a factor of 1.5.