Sensor platforms with active sensing equipment such as radar may betray their existence, by emitting energy that will be intercepted by enemy surveillance sensors. The radar with less emission has more excellent performance of the low probability of intercept(LPI). In order to reduce the emission times of the radar, a novel sensor selection strategy based on an improved interacting multiple model particle filter(IMMPF) tracking method is presented. Firstly the IMMPF tracking method is improved by increasing the weight of the particle which is close to the system state and updating the model probability of every particle. Then a sensor selection approach for LPI takes use of both the target’s maneuverability and the state’s uncertainty to decide the radar’s radiation time. The radar will work only when the target’s maneuverability and the state’s uncertainty exceed the control capability of the passive sensors. Tracking accuracy and LPI performance are demonstrated in the Monte Carlo simulations. Sensor platforms with active sensing equipment such as radar may betray their existence, by emitting energy that will be intercepted by enemy surveillance sensors. The radar with less emission has more excellent performance of the low probability of intercept (LPI). In order to reduce the emission times of the radar, a novel sensor selection strategy based on an improved interacting multiple model particle filter (IMMPF) tracking method is presented. updating the model probability of every particle. Then a sensor selection approach for LPI takes use of both of the target’s maneuverability and the state’s uncertainty to decide the radar’s radiation time. The radar will work only when the target’s maneuverability and the state’s uncertainty exceeds the control capability of the passive sensors. Tracking accuracy and LPI performance are demonstrated in the Monte Carlo si mulations.