To solve the problem of location inaccuracy in single-observer airborne passive location caused by outliers, a robust constrained total least squares (RCTLS) algorithm was proposed. First, the airborne passive location model was established, and weighted constrained total least squares (WCTLS) location criterion was obtained, which could be solved by the Newton’s method. Then, the robust extremal function for WCTLS criterion was built according to generalized Mestimation principle, thus converting the RCTLS problem to the design of equivalent weight function. The equivalent weight function was built based on Danish method. Theoretical analyses indicate that the RCTLS algorithm can identify outliers effectively, and reduce weights of abnormal measurement data in order to reduce their influence on location result. Simulations show that when outliers exist, the RCTLS algorithm keeps an ideal estimation, which proves that the RCTLS algorithm is more robust.