System trade-offs in a swept source FMCW LiDAR with dispersive OPA beam steering

Abstract

A solid-state FMCW LiDAR system on a photonic chip can be subdivided into its scanning engine and ranging engine. The scanning engine consists of the laser source and beam steering optics, while the ranging engine consists of a modulated transmitted signal and a coherent receiver. Here, we present the practical considerations of using the wavelength of a swept laser source for both FMCW ranging and beam steering through a dispersive optical phased array (DOPA). Controlling both functions with a single variable (the laser wavelength) is very attractive from a system perspective. The DOPA maps the wavelength injected in its input port to a unique spot in the far-field. Thanks to reciprocity, this mapping also works in reverse and so the reflected beam is sent back to the same input port. Consequently, the DOPA not only provides a simple mechanism for the steering and receiving optics, but also a strong rejection of unwanted signals, since the DOPA acts both as a spatial and a spectral filter. Steering based on sweeping the wavelength can be combined with the frequency ramping for FMCW ranging. The sweep rate and tuning range of the laser determines the far-field coverage, as well as the depth resolution and precision of the ranging engine. The design freedom of the system can be extended by feeding multiple lasers in parallel into the DOPA, without the need for extra wavelength filters. The use of multiple lasers simultaneously (each illuminating different far-field locations), combined with the discretized DOPA architecture, represents a promising approach to system scalability. We analyze the trade-offs and constraints arising in our system, due to the coupling of the parameters of the scanning engine and the ranging engine. In addition, we model the imperfections along the path of the optical signal, starting from its generation by the tunable laser up to its detection on the coherent receiver. The model is then used to analyze the impact of the system parameters on the LiDAR performance metrics.