# Adaptive Suppression Method of LiDAR Background Noise Based on Threshold Detection
## 3 Adaptive Suppression Method of Background Noise  
### Structure and Implementation  
There are two main methods of CFAR control in LiDAR: one is to adjust the reverse bias voltage of the APD to change its multiplication factor, so that the noise amplitude of the system remains stable; the other is to adjust the threshold voltage of the signal discrimination comparator. The first method often requires ms-level response time due to the bandwidth limitation of the low-pass filter network of the high-voltage power supply,and the single detection time of the LiDAR is mostly us-level during real-time scanning, so the adjustment is generally based on the average background noise of the whole scanning field of view, which cannot meet the demand of fast adjustment of the background noise change in the single detection. Compared with the first method, the signal detection threshold network has a larger bandwidth, and the response speed can reach ns-level. Therefore, the false alarm caused by fast variable background noise can be effectively solved by adaptive adjustment of the signal detection threshold.  
The implementation structure of the adaptive method is shown in Figure 5, which is mainly composed of a noise quantization unit, threshold adjustment unit and signal processing unit. The noise quantization unit is used to detect and quantify the received noise rapidly. According to the detection noise in the receiver, the threshold adjustment unit adjusts the signal identification threshold voltage \(\mathrm{V_{T_{S}}}\) and noise identification threshold voltage \(\mathrm{V_{T_{S}}}\) through the cascaded voltage network. In addition to completing the traditional APD bias control, the signal processing unit also receives the output of the noise detection unit during single pulse detection and controls the DAC to correct the signal threshold voltage according to the noise quantization value.  
The implementation of the adaptive method can be divided into two stages. During the LiDAR operation, it can be divided into two periods, before the time of light emission \(\mathrm{T_{1}}\) and after the time \(\mathrm{T_{2}}\), according to the working state of the laser, as shown in Figure 6. At the beginning of each detection, the system generates a pulse laser emission command. After receiving the pump signal of the excitation source, the laser needs a period of time \(\mathrm{T_{1}}\) to make the working material in the optical resonator achieve complete particle number reversal and then output the laser. At this time, the detection-varied background noise is not affected by the laser, and the system-ranging measurement window is closed, which is helpful to quantize background noise and adjust the threshold of signal identification. Therefore, the adjustment circuit compares and quantifies the noise quickly through the noise quantization unit during the time \(\mathrm{T_{1}}\) and controls the cascade network to complete the rapid adjustment of the signal threshold voltage. In a single detection, the power of background noise will continue to float for the moving target. Therefore, when the threshold voltage is rapidly adjusted by the cascade network, the noise quantization unit will continue to work during the detection time \(\mathrm{T_{2}}\), and the quantized result will be recorded in the signal processing unit as the correction value. The DAC is controlled by the signal processing unit to change the reference voltage \(\mathrm{V_{ref}}\) of the cascade network, which simultaneously realizes the correction of the signal detection threshold voltage \(\mathrm{V_{T_{S}}}\) and noise detection threshold voltage \(\mathrm{V_{T_{S}}}\).  
Figure 5: Adaptive suppression background noise implementation structure.