Objective Geiger-mode avalanche photodiode (Gm-APD) arrays have single- photon sensitivity and each pixel can detect the echo photons independently. Lidar systems based on Gm-APD arrays have many advantages, including high imaging resolution, fast imaging rate and possibilities of using lower power laser as the transmitter hence reducing the overall system size, weight, and power (SWaP). These advantages make the Gm-APD array lidar system very suitable for applications in the fields of mobile platform terrain mapping, which have a strict restriction on the total SWaP of the payloads and require a fast imaging rate. In this study, we propose a miniaturized imaging lidar system based on a domestically developed InGaAs 64x64 Gm-APD array. This system uses a large-pixel-format detector array combined with a coaxial scanning mechanism to achieve fast terrain three- dimensional (3D) imaging on vehiclemounted mobile platforms. Methods The system is composed of fiber laser module, detector array module, transceiver module, scanning module and system control module. The 1545 nm laser source can operate at a repetition rate of 25 kHz with a maximum pulse energy of 32 mu J, and the laser pulse width is 4 ns. In order to get a uniform illumination on the targets, the transmitting optics collimate and homogenize the laser pulses, so that the divergence angle of the emitted laser pulses is 8 mrad. The receiving optics collect the echo photons, and a 1-nm-bandwidth filter with a center wavelength of 1545 nm is used to reduce the solar background noise. The InGaAs 64x64 GmAPD array with a detector efficiency of 20% at 1545 nm is adopted to detect the echo photons. Using a 64x64 detector array and a fast scanning unit, and with the help of a moving sensor platform, the system can achieve large- scale terrain mapping. A noise filtering method based on time-domain distribution characteristics of signal and noise is used to remove the noise points in the real-time data. Both static experiments and dynamic imaging experiments were conducted to verify the performance of the system. In static measurement conditions, two flat- panel targets were placed in front of the system at distances of 102. 56 m and 104. 06 m, respectively. Then the standard deviation of points to plane was evaluated for the two targets. In dynamic imaging experiment conditions, the lidar system, position and orientation system (POS), and panoramic camera were installed on a vehicle-mounted mobile platform with a velocity of 60 km/ h to conduct large-scale 3D imaging of the test area. The 3D lidar images of the test area were compared with the Google map results, meanwhile, the area coverage rate and the average measuring point density were evaluated. Results and Discussions The two flat-panel targets at distances of 102. 56 m and 104. 06 m were detected. The time of flight histogram (Fig. 9) shows two peaks with a time difference of 10 ns, and from the 3D image (Fig. 10) the points of the two targets can be clearly identified. The measured distance deviation of the two targets is consistent with the reference distance deviation. The standard deviations of points fit to plane of the measured data are 0. 12 m and 0. 11 m, respectively, and the results for the simulated data are 0. 10 m and 0. 10 m (Fig. 11). In dynamic imaging experiments, the point cloud results of the region near Baisha River Bridge, Qingdao, Shandong Province, were successfully captured at a platform velocity of 60 km/h. The resulting area coverage efficiency was 36 km(2)/h. The partial profiles of the Baisha River Bridge show detailed 3D information about the bridge, and the piers and the street lamps can be clearly identified in the 3D lidar image (Fig. 13). The high-resolution lidar image (Fig. 14) shows a 3D point cloud of the scenic spots along the river and a dam, which has a mean measurement density greater than 13000 points/m(2). The Google map photographs of the same area helped to identify the characteristics of these targets. Conclusions A miniaturized imaging lidar system based on a domestically developed InGaAs 64x64 Gm-APD array is designed, which is capable of achieving fast terrain 3D imaging on a vehicle-mounted mobile platform. Both static experiments and dynamic imaging experiments were conducted to verify the performance of the system. In static measurement conditions, the standard deviation of points to plane for flat targets at a distance of 100 m was 0. 12 m. In dynamic imaging experiment conditions, the 3D point cloud results of the measured area were successfully obtained when the system was mounted on a mobile platform with a velocity of 60 km/ h. The mapping rate was about 36 km(2)/h and the average measuring point density was 13454 points/m(2). The results indicated that the lidar system based on a domestic Gm-APD array can realize topographical remote sensing detection on the mobile platform, providing a new technical means for high- resolution terrain mapping of the high-speed vehicle platform. The development of a smaller and more lightweight Gm-APD array lidar system, which can be mounted on small unmanned aerial vehicles ( UAVs) to conduct complex terrain area mapping missions, will be explored in the future.
