Spectrum sensing is one of the critical features in cognitive radio based dynamic spectrum access networking. In this paper, we discuss a new spectrum sensing technique for primary incumbent detection. The proposed method is based on observing the PHY errors, received signal strength and n-moving window averaging of the observed measurement. The sensing parameters are dynamically optimized based on the operating radio environment. This sensing method is implemented in SpiderRadio, a cognitive radio testbed based on off-the-shelf IEEE 802.11 devices. Experimental results show that the proposed technique results in very low sensing delay and failure probability.