In multisensor target tracking systems, measurements from different sensors on the same target typically exhibit biases. These biases can be accounted for as fixed random variables by the Schmidt-Kalman filter. Furthermore, measurements from the same target can arrive out of sequence. Recently, a procedure for updating the state with a multistep-lag “out-of-sequence” measurement (OOSM) using the simpler “1-step-lag” algorithm was developed for the situation without measurement biases. The present work presents the solution to the combined problem of handling biases from multiple sensors when their measurements arrive out of sequence. The state update with an OOSM is derived first for a KF tracker. This technique is then extended to the case where the tracker is an IMM estimator.