Multiple surface range Estimation in 3D flash imaging ladar via expectation maximization

Multiple surface range estimation has become a challenging in 3D Flash imaging ladar due to the received pulse is corrupted by many factors, such as the optical aberrations from the imaging system, the noise from the detector and the medium through which it is imaging. These factors either cause the scene's intensity to spread, or blur, across pixel or add unwanted and disruptive noise effects. The intensity spreading and noise corrupts the correct pixel intensities at each range gate by mixing intensities with neighboring pixels thereby providing false intensity values and therefore incorrect photon counts to the range estimation. In this paper, we propose an algorithm to enhance the range estimation of multiple surfaces per pixel in 3D Flash imaging ladar. Using this algorithms, we can improve the multiple surface range estimation performance over traditional multiple surface range estimate algorithms. A comparison between the existing methods and the proposed algorithms has been carried out. The simulation results show the efficiency and effectiveness of proposed method over existing algorithms.