Cognitive radio is able to effectively increase spectral utilization. However, cooperative spectrum sensing gives malicious users chances to interfere with its decision processes. If a mobile secondary user's energy detection results become unreliable, conventional trust-value based cooperative spectrum sensing algorithms, which are used to resist malicious attacks, cannot distinguish whether it's caused by a reliable user moving into a deep-fading area or it attacking maliciously. This is the main reason why the detection performances of conventional algorithms are terribly bad when secondary users are mobile. This paper proposes a trust-value based cooperative spectrum sensing algorithm aiming at mobile secondary users. We divide the whole region into cells according to different areas' actual channel conditions so that the detected results of users in any one of cells are very close to each other but those in different cells are quite different. Our proposed approach removes malicious users independently in each cell based upon their trust values. And larger weighting coefficients are given to cells with better channel conditions. Then this paper analyzes the effects of the average velocity of secondary users on the detection performance. Simulation results show that when secondary users are mobile, the detection performance of our algorithm is much better than that of conventional trust-value based cooperative spectrum sensing algorithms proposed for static secondary users and is better than that of a trusted collaborative spectrum sensing for mobile cognitive radio networks based upon location reliability and malicious intention which also takes location channel differences into considerations.