In addressing the challenge of UAV target search under uncertain prior information conditions and with consideration of sensor detection probability and false alarm probability, a probability-adaptive updating strategy for target search is devised. Firstly, a probability map of the uncertain prior environment is established by using the Beta distribution. Subsequently, an adaptive target search probability updating strategy is proposed, enabling the UAV to dynamically adjust detection frequencies based on the probability information map. Furthermore, within the probability updating strategy, a rejection probability correction factor is introduced to dynamically regulate the probability change quantity based on map probability discrepancies, thereby mitigating potential false positives and false negatives in the search task. Finally, numerical simulation experiments validate that the proposed target search adaptive updating strategy can decrease UAV false detection probability effectively without compromising search efficiency.