Feasible Self-Calibration of Larger Field-of-View (FOV) Camera Sensors for the Advanced Driver-Assistance System (ADAS).

This paper proposes a self-calibration method that can be applied for multiple larger field-of-view (FOV) camera models on an advanced driver-assistance system (ADAS). Firstly, the proposed method performs a series of pre-processing steps such as edge detection, length thresholding, and edge grouping for the segregation of robust line candidates from the pool of initial distortion line segments. A novel straightness cost constraint with a cross-entropy loss was imposed on the selected line candidates, thereby exploiting that novel loss to optimize the lens-distortion parameters using the Levenberg-Marquardt (LM) optimization approach. The best-fit distortion parameters are used for the undistortion of an image frame, thereby employing various high-end vision-based tasks on the distortion-rectified frame. In this study, an investigation was carried out on experimental approaches such as parameter sharing between multiple camera systems and model-specific empirical γ -residual rectification factor. The quantitative comparisons were carried out between the proposed method and traditional OpenCV method as well as contemporary state-of-the-art self-calibration techniques on KITTI dataset with synthetically generated distortion ranges. Famous image consistency metrics such as peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and position error in salient points estimation were employed for the performance evaluations. Finally, for a better performance validation of the proposed system on a real-time ADAS platform, a pragmatic approach of qualitative analysis has been conducted through streamlining high-end vision-based tasks such as object detection, localization, and mapping, and auto-parking on undistorted frames.

RF photonic downconversion of vector modulated signals based on a millimeter-wave coupled electrooptic nonlinear polymer phase-modulator.

We report the RF photonic reception and downconversion of vector modulated RF signals using a millimeter-wave coupled electrooptic phase modulator with in-plane slotted patch antennas based on SEO125 nonlinear polymer. We demonstrate experimental results with QPSK, 8-PSK, 16-QAM, 32-QAM, and 64-QAM millimeter-wave signals centered at 36 GHz. After downconversion to intermediate frequencies between 0.5 GHz and 2 GHz, the vector encoded signals are demodulated using an electrical signal analyzer and found to have measured error vector magnitudes below 8%. Design, simulation, fabrication, and experimental results are presented and discussed.