FEATURE AUTOMOTIVE ELECTRONICS LIDAR PERCEPTION CHALLENGES by Sarven Ipek, LIDAR marketing manager A


successful autonomous vehicle is going to have to use a tightly integrated system of sensors to replicate the driving abilities of a human being. The typical human driver uses two eyes, two ears, and the tactile feedback of the car in order to drive. Their brain processes all this information in real time and references their vast database of driving experience. The sensors required to replicate human driving will include radar, LIDAR, cameras, inertial measurement units (IMUs), and ultrasonic sensors. Each of these systems will have its strengths, but also literal blind spots. It is highly unlikely one sensor will ever be so refined as to negate the need for the others. In this article, we are going to look at the top level design considerations for LIDAR, which is a sensor that will provide significant data to any autonomous driving solution.


Looking at the receive path, the signal-to-noise ratio (SNR) of the


system affects the ability to detect small objects at a long distance (100 m to 300 m). The ADC noise floor cannot exceed the other sources of noise in the receive path. If the background light or the signal shot noise contributions are lower than the ADC’s noise floor or the printed circuit board (PCB) noise, the accuracy will be limited. Performing time of flight (ToF) calculations in a direct detect topology demands that the system can output short pulses (~1 ns to 5 ns) and detect them with a high sampling rate ADC. Sampling speeds of 1 GSPS enable this on the receive signal path. Also, keep in mind, the ADC effective number of bits (ENOB) must allow full output range from the transimpedance amplifier (TIA) without clipping the signal. Does the system need to detect a basketball at 100 m away? Determining the reflectivity and size of objects of concern, as well as the distance, limits the acceptable SNR of the TIA. The same pulses that the ADC must detect require that the TIA has a bandwidth that detects narrow pulses. Due to such a wide range of distance, reflectivity, and size of objects that systems must handle, the TIA must be capable of recovering from a saturation event. Saturation events can occur from a highly reflective object returning a high percentage of the light that was transmitted, which saturates the amplifier (for example, a close object like a speed limit sign). These events are common, and the speed at which a system can recover in order to provide accurate information is critical for safety.


LIDAR is a close partner of radar in an autonomous vehicle. Both of these technologies operate without visible light, which is crucial for night driving or low light conditions. Radar is good for long distance detection and tracking, while LIDAR provides higher angular resolution allowing for object recognition and classification. Put another way, radar is good for detecting there might be something out there, while LIDAR can tell you more about that something once the radar finds it. There are technical challenges when designing a LIDAR system, the obvious one being staying below the eye safety limitations for near infrared wavelengths. These safety guidelines are outlined in IEC 60825- 1. This is not to diminish the importance of eye safety—the aspects discussed here all play into decisions that affect eye safety. There are many different LIDAR system topologies, with varying degrees of design complexity, which come with their own advantages and disadvantages. At the core, all designs have the same fundamental aspects that need attention. Let’s focus on considerations other than eye safety that affect system design, namely: maximizing SNR, detection requirements, field of view, thermal considerations, power consumption, and dead reckoning.


The field of view and angular resolution required will also impact


the ability to detect the basketball. Transmit and receive optics are the main contributing components to determine the field of view. Angular resolution will determine whether you can detect and classify an object like a basketball at some farther distance or


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JUNE 2020 | ELECTRONICS


/ ELECTRONICS


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