In this paper, we examine crosstalk effects that can arise in multi-LiDAR configurations, and we show a data-based approach to mitigate these effects. Due to the ability to acquire precise 3D data of the environment, LiDAR-based sensor systems (sensors based on “Light Detection and Ranging”, e.g., laser scanners) increasingly find their way into various applications, e.g. in the automotive sector. However, with an increasing number of LiDAR sensors operating within close vicinity, the problem of potential crosstalk between these devices arises. “Crosstalk” outlines the following effect: In a typical LiDAR-based sensor, short laser pulses are emitted into the scene and the distance between sensor and object is derived from the time measured until an “echo” is received. In case multiple laser pulses of the same wavelength are emitted at the same time, the detector may not be able to distinguish between correct and false matches of laser pulses and echoes, resulting in erroneous range measurements and 3D points. During operation of our own multi-LiDAR sensor system, we were able to observe crosstalk effects in the acquired data. Having compared different spatial filtering approaches for the elimination of erroneous points in the 3D data, we propose a data-based spatio-temporal filtering and show its results, which may be sufficient depending on the application. However, technical solutions are desired for future LiDAR sensors.