A standard method for distance determination is light detection and ranging (LiDAR), which relies on the emission and detection of reflected laser pulses. When LiDAR systems become common for every vehicle, many simultaneous laser signals will produce mutual LiDAR interference between LiDAR systems. In this paper, we analyze the possibility to recognize mutual interference in time-correlated single photon counting (TCSPC) LiDAR with particular focus on flash systems. We evaluate the LiDAR interference appearance by deriving the expected event distribution for ego and aggressor signal. From that, we calculate the probability of photon detection within each measured signal. This paper shows the high potential of different pulse repetition frequencies to reduce LiDAR interference. Using signal-to-noise ratio (SNR), we define the extinction distance, beyond which the aggressor signal completely extinguishes the ego signal. Applied on different background and laser event rates, we find the connection between ideal LiDAR system designs and lowest probability for unrecognized LiDAR interference. Furthermore, we show the relationship to a specific LiDAR design, which must fulfill eye safety condition and receives lower intensities with increasing target distances. Finally, we present different solutions for the recognition and reduction of LiDAR interference based on our previous results. Index Terms-Light detection and ranging (LiDAR), mutual LiDAR interference, time-correlated single-photon counting (TCSPC), direct time-of-flight (dTOF).
Autonomous driving can make traffic safer by reducing human errors. Different sensor types in autonomous vehicles could introduce additional technical failures. We offer a target simulator testing LiDAR systems under automotive conditions. Therefore, data are projected over-the-air by laser signals on the LiDAR detector. This work presents a concept of a LiDAR target simulator with regards to LiDAR systems using the direct timeof-flight principle. We develope design considerations for a screen discussing undesired screen reflections, a curved screen form and the positioning of light sources on this screen. As one main solution, we introduce a concept of an antireflective screen. For the scenario simulation, we derive a model delivering the required optical power representing a simulated target, which is combined with the simulated time-of-flight. Considering no prior knowledge of the LiDAR system under test, we discuss the required calibration data and timing resolution. Thereby, we suggest an optimized time-of-flight concept requiring only one optical trigger to determine the LiDAR measurement start. All requirements are supported by calculated example parameters based on real LiDAR systems. Altogether, we discuss main challenges and possible solutions of our LiDAR target simulator, which will allow a safer and more efficient development of LiDAR systems. Index Terms-Time-of-flight (ToF), light detection and ranging (LiDAR) testing, LiDAR target simulator, device-under-test (DUT), LiDAR-under-test (LUT), hardware-in-the-loop (HiL), over-theair (OTA).
The increased use of light detection and ranging (LiDAR) systems for distance determination requires the investigation of mutual interference. In this paper, we describe the conditions for occurrence of LiDAR interference. We outline suppression methods for different LiDAR types identifying pulse-position modulation (PPM) as solution for time-of-flight LiDAR with time-correlated single photon counting (TCSPC) histograms. Based on PPM, we present a suppression method, which randomly varies the laser pulse emission times. For optimal suppression, we switch on the suppression only when interference is present. To recognize the occurrence of LiDAR interference, we develop a multi-pulse detection algorithm that can also extract all pulse positions. Simulations show that the algorithm can be applied for a signal-to-noise ratio greater than 3. Determining the heights of all recognized pulse signatures, an appropriate suppression level can be chosen. We successfully show the optimized interference suppression for an example LiDAR measurement. For a safe use by multiple systems, we suggest random numbers. We reuse the TCSPC histograms to generate random numbers, whose generation probability is calculated theoretically and confirmed by simulation and measurement data. For nearly all histogram distributions consisting of background-and laser-generated data, a sufficient amount of random numbers is produced.
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