In unknown environments, it is difficult for mobile robots to precisely understand the obstacle distribution and effectively search the target. This paper proposes a heuristic navigation method based on LiDAR. First, the rising/falling edges are introduced in LiDAR-data to define and detect obstacles' edges, and the edge matching algorithm is designed to recognize the narrow gaps and continuous obstacles. After the gap removal and obstacle expansion, the continuous obstacle set is obtained to describe the surrounding environment. Second, facing the obstacle that blocks the target, a heuristic selection method for temporary targets is proposed and the switching condition is designed, which make the robot avoid each kind of obstacle in advance with a shorter path, and reach the target progressively. Simulations and comparisons based on Matlab are conducted, whose results show that the proposed method greatly improves the traffic efficiency, path smoothness and global searching ability of mobile robots in unknown environments. The proposed method is also implemented in experiments based on ROS to verify its effectiveness in real environments.