# Adaptive Suppression Method of LiDAR Background Noise Based on Threshold Detection
## 3 Adaptive Suppression Method of Background Noise
### Critical Modules Implementation
#### 3.2.2 Threshold Adjustment  
The adjustment of the signal threshold is self-adaptive through a cascaded network of current-type architecture and DAC output voltage, as shown in Figure 8. The adaptive process is divided into two steps. Firstly, the current source network is controlled to rapidly adjust the signal threshold voltage according to the quantization value of noise detection in time T\({}_{1}\). Secondly, the noise quantization unit continues to work in time T\({}_{2}\). The quantization result is taken as the correction value. After this detection, the DAC is controlled by the signal processing unit to adjust the reference voltage V\({}_{\text{ref}}\) of the current source network to achieve the correction of the threshold voltage V\({}_{\text{Ts}}\) and V\({}_{\text{Tn}}\).  
Since the signal threshold regulation time is very short in ns-level, the design uses current steering architecture to achieve fast change in the signal threshold. It controls the current source through the switch for stacking output and can directly drive the resistive load without the buffer circuit of the resistance voltage divider network, thus avoiding the establishment time of the buffer circuit and providing high-speed regulation. The correction function of DAC is realized by changing the input bias voltage of the current source array. The reference voltage provided by the DAC is first converted to reference current, and then converted by the bias circuit to the input bias voltage of the current source array. Therefore, through the interaction of the circuit, the correction function is realized.  
The current source is a sleeve structure composed of CMOS with high output impedance. The current source is controlled by a switch and ideally its output current is  
\[V_{\text{Ts}}=I_{out}R_{T}=\sum_{k=0}^{N-1}b_{k}I_{ref}R_{T} \tag{17}\]  
where I\({}_{\text{out}}\) is the output current, R\({}_{\text{T}}\) is the load impedance, k is the number of current sources connected to the load, and I\({}_{\text{ref}}\) is the reference current. Additionally, the number of current sources determines the variation range of FAR during rapid adjustment. The reference current I\({}_{\text{ref}}\) is controlled by V\({}_{\text{ref}}\) of the DAC.  
The adjustment of threshold value can be determined by the FAR and detection probability requirement of the system. Assuming that the detection threshold cannot exceed the maximum false alarm probability required by the system as P\({}_{\text{Fmax}}\), according to the FAR Formula (7), under no signal, the following can be obtained:  
\[P_{\text{Fmax}}\geq\frac{1}{2}-\frac{1}{2}\text{er}f(\frac{V_{\text{Ts}}-(R_{ \text{p}}P_{b}+I_{d})G}{\sqrt{2V_{n}}}) \tag{18}\]  
\[V_{\text{Ts}}\geq\sqrt{2V_{n}}erf^{-1}(1-2P_{F\text{max}})+(R_{\text{p}}P_{b} +I_{d})G \tag{19}\]  
The threshold voltage is related to the designed FAR of the system. According to the parameters in Table 1, when the FAR is set at 0.1%, the simulation result is shown in Figure 9, and the optimal value of the detection threshold V\({}_{\text{Ts}}\) should be taken at the intersection of the simulation result surface and the plane of the designed FAR.  
Figure 8: Threshold adjustment cascade architecture.