Two sound localization algorithms based on the head-related transfer function were developed. Each of them uses the interaural time delay, interaural level difference, and monaural spectral cues to estimate the location of a sound source. Given that most localization algorithms will be required to function in background noise, the localization performance of one of the algorithms was tested at signal-to-noise ratios (SNRs) from 40to−40dB. Stimuli included ten real-world, broadband sounds located at 5° intervals in azimuth and at 0° elevation. Both two- and four-microphone versions of the algorithm were implemented to localize sounds to 5° precision. The two-microphone version of the algorithm exhibited less than 2° mean localization error at SNRs of 20dB and greater, and the four-microphone version committed approximately 1° mean error at SNRs of 10dB or greater. Potential enhancements and applications of the algorithm are discussed.