Data Processing Approaches on SPAD-Based d-TOF LiDAR Systems: A Review

Abstract

With the rise of advanced driver assistance systems (ADAS), range sensors and their data processing methods are becoming more and more important. Light detection and ranging (LiDAR) sensors are attracting attention due to their unique advantages in terms of radial distance resolution and detection range. However, the study of LiDAR data processing is usually divorced from the LiDAR sensor measurement process itself. This leads to critical measurement information being overlooked. This paper seeks a breakthrough to improve the performance of singlephoton-avalanche-diode-based direct time-of-flight LiDAR systems by reviewing the data processing stages and corresponding processing approaches for LiDAR measurements, starting from photon incidence and ending with high-level feature recognition. Firstly, we propose a LiDAR system model based on data generation and transfer. The data forms in such a LiDAR system are mainly classified into timestamps, time-correlated histograms, point cloud data, and high-level properties. Subsequently, data processing methods applied to each of these data forms are analyzed. A number of hardware solutions closely related to data transmission and control are also included in the discussion. The principles, limitations, and challenges of these methods are discussed in detail and the criteria for evaluation of time-correlated histograms in ADAS are proposed. Finally, the research gaps in data processing are summarized, and future directions for research development are presented.

Direct Time-of-Flight Single-Photon Imaging

“…The histogram usually requires a large number of bins set by the maximum round trip time divided by the time resolution. dToF provides a simple discrimination of multipath echoes by suitable interpretation of the multiple peaks within the ToF histogram [8][9] (Fig. 2).…”

Enhanced visual perception through photon counting and computational imaging: what the time and number of photon events can tell us about the world around us

“…Single photon counting works best when the probability to detect a photon is far below "1" (when detection is improbable). This sensing approach is opening new applications in time correlated single photon-counting (TCSPC) 3 such as ranging with ultra low laser powers 4,5 and timing of ultra fast processes as in fluorescence lifetime imaging microscopy (FLIM). 6,7 Further, these capabilities enable the realization of novel computational sensing approaches such as non-line of sight (NLOS) sensing [8][9][10] which expands the perception range of optical sensors to areas outside the direct line-of-sight.…”

2-D Optical-CDMA Modulation With Hard-Limiting for Automotive Time-of-Flight LiDAR

“…Studies have been performed on characterizing and improving the hardware aspects and processing techniques of this kind of pulsed-ToF systems. For example, Chen, et al [4] reviewed existing data processing approaches and workflows on SPAD-based ToF LiDAR systems and then suggested future research directions. Donati, et al [5] developed a theoretical framework to evaluate the precision of ToF measurements by analyzing the timing errors in APD-and SPAD-based receivers.…”