In advanced driver-assistance systems, LiDAR data are used for range detection and obstacle avoidance in combination with other sensors. The frame rate of a LiDAR sensor corresponds to the data availability that is crucial for efficient data fusion. In 1D micro-scanning LiDAR, pixel accumulation is introduced to increase data signal-to-noise ratio and typically performed a fixed number of times that directly affects pixel acquisition time and frame rate. In this paper, we present an adaptive pixel accumulation algorithm that not only reduces required on-chip memory array by compressing LiDAR raw data, but also increases data availability for occupancy grid computation by enabling an early peak detection and eliminating unnecessary accumulation cycles whenever possible. We implemented this concept on FPGA and compared its efficiency with a state-of-the-art approach. Presented simulation and measurement results show an improvement of data availability in short and mid-range scenarios or when detecting a highly reflective target.
|Title of host publication||2021 24th Euromicro Conference on Digital System Design (DSD)|
|Publication status||Published - 2021|
|Event||24th Euromicro Conference on Digital System Design: DSD 2021 - Virtuell, Austria|
Duration: 1 Sep 2021 → 3 Sep 2021
|Conference||24th Euromicro Conference on Digital System Design|
|Abbreviated title||DSD 2021|
|Period||1/09/21 → 3/09/21|