Phase calibration for integrated optical phased arrays using artificial neural network with resolved phase ambiguity

Abstract

Phase calibration for optical phased arrays (OPAs) is a key process to compensate for the phase deviation and retrieve the initial working state. Conventional calibration approaches based on iterative optimization algorithms are tedious and time-consuming. The essential difficulty of such a problem is to inversely solve for the phase error distribution among OPA elements from the far-field pattern of an OPA. Deep-learning-based technology might offer an alternative approach without explicitly knowing the inverse solution. However, we find that the phase ambiguities, including conjugate ambiguity and periodic ambiguity, severely deter the accuracy and efficacy of deep-learning-based calibration. Device-physics-based analysis reveals the causes of the phase ambiguities, which can be resolved by creating a tailored artificial neural network with phase-masked far-field patterns in a conjugate pair and constructing a periodic continuity-preserving loss function. Through the ambiguity-resolved neural network, we can extract phase error distribution in an OPA and calibrate the device in a rapid, noniterative manner from the measured far-field patterns. The proposed approach is experimentally verified. Pure main-beam profiles with > 12 dB sidelobe suppression ratios are observed. This approach can help overcome a crucial bottleneck for the further advance of OPAs in a variety of applications such as lidar.

High-Precision Silicon-Integrated Frequency-Modulated Continuous Wave LiDAR Calibrated Using a Microresonator

“…In addition, for the scheme proposed in this study, the measurement distance mainly depends on the laser power and the transceiver lens group, which can achieve high accuracy absolute measurement in the order of several kilometers or even a hundred kilometers if high-power EDFA and large-aperture telescope system are used . Now, with the rapid development of on-chip devices such as lens-assisted beam steering (LABS) , and optical phased array (OPA), , it can achieve beam steering. If combined with the scheme proposed in this study, it is expected to realize a more integrated on-chip LiDAR with long distance and high precision.…”

Dynamic Measurement with High Precision Using Frequency Agile Spatial Encoding Integrated FMCW LiDAR

“…This study proposes that FASE-FMCW LiDAR can dynamically adjust the coding range based on the estimated target velocity, aiming to broaden its application prospects for faster velocities and longer distances . Moreover, by integrating advanced beam scanning devices such as Lens-Assisted Beam Steering (LABS) , and Optical Phased Array (OPA), , it is anticipated to achieve three-dimensional dynamic velocity-distance synchronous measurements and imaging, , meeting the measurement requirements and applications in wide-area global complex scenes. , …”

Silicon-Based Polarization-Insensitive Optical Antenna Design and Experimental Characterization of Optical Phased Arrays

“…Different techniques can be used to align the phases. Phase calibration using optimization-based methods [66], [67] or interferencebased method [60]have been presented and similar technique can also be implemented on the OPA under testing using the designed far-field imaging setup. Following the alignment of the phase fronts, the steerability of the OPA can also be examined by changing the phases of individual antenna to create controlled phase offsets among individual antennas.…”