A large-scale coherent 4D imaging sensor

Detailed and accurate three-dimensional (3D) mapping of dynamic environments is essential for machines to interface with their surroundings, and for human-machine interaction. Although considerable effort has been spent to create the equivalent of the CMOS image sensor for the 3D world, scalable, high-performance, reliable solutions have proven elusive. Focal plane array (FPA) sensors using frequency modulated continuous wave (FMCW) light detection and ranging (LiDAR) have shown potential to meet all the requirements and also provide direct measurement of radial velocity as a fourth dimension (4D). Prior demonstrations, while promising, have not achieved the simultaneous scale and performance required by commercial applications. In this paper, we present a large-scale, coherent LiDAR FPA enabled by comprehensive chip-scale optoelectronic integration. A 4D imaging camera is built around the FPA and used to acquire point clouds. At the core is a 352x176 pixel two-dimensional FMCW LiDAR FP..., , # A large-scale coherent 4D imaging sensor

Dataset DOI: [10.5061/dryad.6t1g1jxcm](https://doi.org/10.5061/dryad.6t1g1jxcm)

## Description of the data and file structure

All the data that was used to generate the figures in the publication is included in the attached archive file (.zip).

There are multiple folders in the archive file. Name of the folders match the Figures from the associated manuscript. (i. e. data from Figure 3c is in the folder named \"Fig_3c\")

In each folder, there are datasets (in .csv form) and Python scripts in Jupyter Notebook form (when necessary). When these scripts are run together with the corresponding data from the same directory, they generate the figures in the paper that match the folder name.

Note: There is no data affiliated with Fig. 1 and Fig. 2 available.

Below are the summary of the data from the main text figures existing in the archive.

Folder \"Fig_3a\": .csv data together with Jupyter Notebook that generate the pointcloud in Fig 3a. The col...,