A LiDAR Architecture Based on Indirect ToF For Autonomous Cars

— A LiDAR architecture for autonomous cars is presented and validated by numerical and experimental results. The proposed scheme is based on indirect time-of-flight principle based on continuous-wave pseudorandom codes and incoherent detection for range evaluation. The range ambiguity and resolution are controlled by the parameters of the pseudorandom code. Experimental results are reported for target detection ranging from 13 to 1,000 m, as well as a demonstration of a dual-target detection, demonstrating the efficiency of the proposed LiDAR architecture to operate in real scenarios of autonomous cars. A measured range error of less than 0.6 % has been achieved for both single and dual-target detection.

of techniques for LiDAR range sensing have been proposed [15]- [20]. Most LiDARs applied to autonomous cars are based on the time-of-flight (ToF) principle, which might be categorized in indirect (i-ToF) or direct (d-ToF) according to the range calculation procedure [16]. The i-ToF technique uses the phase difference between periodic signals to determine targets distance [17]- [19] and d-ToF the round-trip time of a single, high peak power short pulse emission [16], [3].
An optical code division multiple access (CDMA) modulation scheme derived from optical orthogonal codes (OOC) was reported in [16] for automotive d-ToF systems. The influence of OOCs design parameters was evaluated and compared to standard single pulses transmission. In [17], a LiDAR architecture base on pseudorandom noise (PN) codes and periodic pulses modulation scheme was proposed to simultaneously determine the target range and speed. This was achieved by exploring the time-of-flight and Doppler effect principles. The authors in [18] presented a LiDAR and freespace optical communication system using a single architecture based on coherent detection. The LiDAR operation principle is similar to [17] with PN sequences and phase difference correlation for range measurement. In [19] Torun et al. proposed a multi-tone continuous-wave LiDAR with multiple fixed RF tones for range and speed information retrieval. Finally, LiDARs photonic integration circuits (PIC) technology have been proposed for cost and size reduction to realize chip-scale systems.
An optical phased array (OPA) applied to autonomous cars LiDAR was designed, fabricated and characterized in [4]. Integrated OPAs with 2-D and 3-D LiDARs performance results were reported in [20].
In this paper, we propose and implement a LiDAR architecture for autonomous cars application based on indirect time-of-flight principle with continuous-wave pseudorandom codes and incoherent detection for range retrieval. Additionally, the proposed work is based on standard telecommunication components, allowing its use for detection and ranging application and data transmission for communication purposes as free-space optics (FSO) systems. Section II discusses the proposed LiDAR architecture and the obtained numerical results. An experimental setup has been conceived and evaluated as presented in Section III. Finally, conclusions and final comments are outlined in Section IV.

II. LIDAR OPERATION PRINCIPLE AND NUMERICAL RESULTS
A schematic of the proposed LiDAR architecture based on work in [18] is shown in Fig. 1. In summary, a continuous wave (CW) laser is modulated in amplitude by a pseudorandom code and transmitted to the target using a collimator or telescope lenses. The target reflected light is coupled into a fiber, photodetected and post-processed to obtain the target range information. The unambiguous range and resolution values depend on pseudorandom code parameters as bitrate and bit sequence duration. The LiDAR system might be divided into three main blocks named signal generator, signal receiver and signal processing. The signal generator block is formed by a CW laser source operating at 1550 nm, whose amplitude is externally modulated in a Mach-Zehnder modulator (MZM) biased at its quadrature point. A bit pattern generator (BPG) drives a pseudorandom bit sequence (PRBS) into MZM as a modulation signal. A sample of the PRBS signal is sent to the signal processing unit for the phase difference calculation step. The modulated laser light is then transmitted to the target. In the signal receiver section, a PIN photodiode converts the reflected light into an electrical signal which is amplified by a low noise amplifier (LNA). At the signal processing chain, the LNA output is digitized by an analog to digital converter (ADC) and post-processed with the PRBS sample to gather the range information. As the transmitted optical signal travels at the speed of light in the free-space, the relation between range distance R and round-trip time τ is given by: The round-trip time τ is determined by the cross-correlation between the PRBS sample and the processed backscattered optical signal. The cross-correlation peak gives the delay experienced by the target reflected signal. Besides, PRBS parameters define the range resolution and unambiguous range [18]. The range resolution ΔR is related to the PRBS bit rate, i.e., modulation bandwidth (BW), by: and the PRBS length multiplied by bit duration defines the repetition interval RI, which determines the unambiguous range Rua.
Numerical analysis has been performed in Optisystem® using the setup presented in Fig The signal processing step has been realized in Matlab® using the transmitted and received PRBS sequence as inputs. A calculation routine has been conceived to resolve the cross-correlation operation and establish the round-trip time τ. The range estimation as a function of cross-correlation level is obtained using (1). First, the setup in Fig. 2 is simulated for a range of 880 m. The transmitted and received PRBS sequence is analyzed in Matlab and the cross-correlation result is shown in Fig.   3(a). The cross-correlation peak is at 880.01 m, validating the proposed LiDAR architecture numerically. A scenario with two targets, i.e., two reflected signals, has also been analyzed. In this case, the transmitted signal is split into two branches and sent to two different delay paths equivalent to 400 and 880 m. In Fig. 3(b) is noticed two cross-correlation peaks at 400 and 880.01 m as expected.
Therefore, the proposed LiDAR architecture has been numerically validated for single and dual-target detection conditions. Some measurements have been carried out with setup from Fig. 4 aiming to demonstrate its performance. First, a back-to-back measurement has been performed to evaluate the setup inherent delay. Fig. 5(a) reports the obtained setup delay with a cross-correlation peak at 6.98 m. Therefore, in the following results, this value is subtracted from the measurements to obtain only the SMF delay value. Applying an 880 m SMF spool in the LiDAR setup, the measured result is shown in Fig. 5(b).
The obtained cross-correlation peak was at 880.36 m, representing a measured error of only 0.04 %.
Additionally, some patch cords and another SMF spool have also been tested and the obtained results are summarized in Table I Table I, it is shown a comparison between the obtained results with the proposed LiDAR and a commercial optical time-domain reflectometer (OTDR).    As numerically evaluated in the previous section, a dual-target condition has been conducted in the experimental setup. In this scenario, the transmitted signal is split into two branches by an optical splitter and two different paths are used to produce distinct delays. In the reception, these two different delayed signals are combined again by an optical combiner. The photodetected signal is digitized and analyzed as a single signal, but with two different delay information.
Again, a back-to-back measurement has been performed to account for the LiDAR system inherent delay, as presented in Fig. 6(a). A propagation delay equivalent to 16.48 m was obtained with this new setup due to the addition of optical splitter and combiner. In Fig. 6  presented LiDAR architecture is based on telecommunication setup and components; therefore, it could be applied as an FSO system for communication purposes. In order to avoid high peak power short time pulse emission presented in conventional ToF, the proposed work presents a modulation code to retrieve the range information in a similar manner implemented by [16], [17], and [19].
However, the modulation technique implemented in [16] has the purpose of avoidance high peak power pulses and provide a coded system to improve its robustness, although the detection technique is direct ToF. The use of indirect ToF techniques and modulation codes have the ambiguity range characteristic, which can be controlled by modulation code parameters as a system variable. For autonomous car applications, besides ranging information, it is important to retrieve speed information as reported by [17] and [19] to provide an improved solution. Although the proposed architecture does not allow gathering the speed information, it is possible to implement this feature by modifying the schematic shown in Fig. 1 as presented by [16]. IV. CONCLUSIONS It has been presented a LiDAR architecture for detection and ranging based on indirect time-offlight implemented by modulation codes with pseudorandom bit sequences, eliminating the need for high peak power short time pulse emission. Besides, the proposed LiDAR architecture is based on telecommunication setup and it is possible to extend its use for communication purposes by means of an FSO system. Regarding its application, the proposed work might be used in autonomous car scenarios as an alternative for detection and ranging implementation. Additionally, the proposed architecture can be modified and updated to retrieve speed information from the measured data.
Numerical simulations and experiments have been carried out in a controlled environment to demonstrate the efficiency of the proposed LiDAR architecture. In this manner, the proposed work has been evaluated for targets ranging from 13 to 1,000 m using single-mode fibers as a propagation medium. Additionally, single and dual-target detection have been reported with a measurement error of less than 0.6 %. Future works regard the implementation of experiments with free-space optics using collimators and plano-convex spherical lenses for optical signal transmission and reception.