Overview: The detection of the information out of sight is always a difficult problem. It is valuable in complex scene such as autopilot and rescue. The casualty would be fewer if we obtain more decision time by getting the information of invisible area in advance. With the development of photoelectric technology, ultrafast lasers and detectors with high sensitivity and time resolution are invented, such as streak cameras, single photon avalanche diodes, superconducting nanowire single-photon detectors, and so on. It is possible to measure the time information of laser pulses in a photon by the single photon detector. The laser pulses can illuminate the scene of non-line-of-sight by bouncing on the relay surface and scattered back to relay surface again. The time of flight that pulses spent in the hidden area and the light intensity distribution on relay surface can be measured by the single photon detector, and the scene out of sight can be depicted from them. The back-projection algorithm, light-cone transform algorithm, Fermat flow and phase-field virtual wave optics have been proposed to calculate the scene out of sight. In order to obtain the light intensity distribution, the relay wall need to be scanned with the methods mentioned above and it is time-consuming. In most application environment, non-line-of-sight information needs to be acquired rapidly and the motion state of moving objects is more useful than their details. In the previous studies, the optical signal scattered by hidden targets is fitted into the Gauss distribution to extract the time of flight, and its position is figured out according to the time of flight. In this paper, we replace the Gauss fitting algorithm with the filtering algorithm to overcome its instabilities and improve the automation of that locating algorithm. Mean filter, medium filter and Gauss filter are proposed to improve the locating performance. In order to compare the characteristics of these three filters, the non-line-of-sight location is simulated with numerical simulation software based on the photon flight model which is optimized with photometry. Medium filter performs better than other two methods in a narrow application environment to obtain the more accurate locating result. For mean filter and Gauss filter, 0.5 m is a suitable distance between the laser source and detectors to locate the target reliable. As to Gauss filter, the position of target can be judged more accurately by probability weighting with an optimized threshold. The applicability of the fitting method and filtering methods are analyzed by comparing the locating error of 25 positions in the area of 5 m×5 m. Location information obtained by the Gauss fitting method is more stable than other two methods. In terms of the average of positioning error, medium filter performs better than other two methods. And the locating result of the fitting method is not accurate and stable as the filtering method.