Measurement Modeling and Performance Analysis of a Bionic Polarimetric Imaging Navigation Sensor Using Rayleigh Scattering to Generate Scattered Sunlight.

The bionic polarimetric imaging navigation sensor (BPINS) is a navigation sensor that provides absolute heading, and it is of practical engineering significance to model the measurement error of BPINS. The existing BPINSs are still modeled using photodiode-based measurements rather than imaging measurements and are not modeled systematically enough. This paper proposes a measurement performance analysis method of BPINS that takes into account the geometric and polarization errors of the optical system. Firstly, the key error factors affecting the overall measurement performance of BPINS are investigated, and the Stokes vector-based measurement error model of BPINS is introduced. Secondly, based on its measurement error model, the effect of the error source on the measurement performance of BPINS is quantitatively analyzed using Rayleigh scattering to generate scattered sunlight as a known incident light source. The numerical results show that in angle of E-vector (AoE) measurement, the coordinate deviation of the principal point has a greater impact, followed by grayscale response inconsistency of CMOS and integration angle error of micro-polarization array, and finally lens attenuation; in degree of linear polarization (DoLP) measurement, the grayscale response inconsistency of CMOS has a more significant impact. This finding can accurately guide the subsequent calibration of BPINS, and the quantitative results provide an important theoretical reference for its optimal design.

One-Pot Synthesis of 2,5-Furandicarboxylic Acid from 2-Furoic Acid by a Pd-catalyzed Bromination-Hydroxycarbonylation Tandem Reaction in Acetate Buffer.

The one-pot synthesis of 2,5-furandicarboxylic acid from 2-furoic acid with a yield of 57 % was achieved for the first time using a Pd-catalyzed bromination-hydroxycarbonylation tandem reaction in HOAc-NaOAc buffer. This synthetic protocol shows major improvements compared to previously reported methods, such as using biomass-based 2-furoic acid as low-cost raw material, one-pot synthesis without isolation of intermediate products, and no need for an acidification procedure. Experiments indicate that the involved Xantphos-modified Pd-catalyst and the buffer solution play significant promoting roles for each individual reaction whereas Br2 (as the brominating reagent) had a negative effect on the second hydroxycarbonylation step, while CO was deleterious for the first bromination step. Hence, in this practical one-pot synthesis, Br2 should be consumed in the first bromination step as fully as possible, and CO is introduced after the first bromination step has been completed.

Measurement error model of the bio-inspired polarization imaging orientation sensor.

This article studies the measurement error model and calibration method of the bio-inspired polarization imaging orientation sensor (BPIOS), which has important engineering significance for promoting bio-inspired polarization navigation. Firstly, we systematically analyzed the measurement errors in the imaging process of polarized skylight and accurately established an error model of BPIOS based on Stokes vector. Secondly, using the simulated Rayleigh skylight as the incident surface light source, the influence of multi-source factors on the measurement accuracy of BPIOS is quantitatively given for the first time. These simulation results can guide the later calibration of BPIOS. We then proposed a calibration method of BPIOS based on geometric parameters and the Mueller matrix of the optical system and conducted an indoor calibration experiment. Experimental results show that the measurement accuracy of the calibrated BPIOS can reach 0.136°. Finally, the outdoor performance of BPIOS is studied. Outdoor dynamic performance test and field compensation were performed. Outdoor results show that the heading accuracy of BPIOS is 0.667°.

Cooperative Catalysis of Ru(III)-Porphyrin in CO2 -Involved Synthesis of Oxazolidinones.

CO2 -transformations into high value-added products have become a fascinating area in green chemistry. Herein, a Ru(III)-porphyrin catalyst (RuCl3 ⋅ 3H2 O-H2 TPP) was found highly efficient in the three-component reaction of CO2 , aliphatic amines and dichloroethane (or its derivative) for synthesis of oxazolidinones in the yields of 71∼91%. It was indicated by means of the control experiments and UV-vis spectra that CO2 was stoichiometrically activated by the involved aliphatic amine substrates to form a stable carbamate salt while 1,2-dichloroethane (or its derivative) was independently activated by the involved Ru(III)-porphyrin catalyst. The combination of CO2 -activation by aliphatic amines with 1,2-dichloroethane activation by Ru(III)-porphyrin catalyst cooperatively contributed to this successful transformation.

Lane detection in dense fog using a polarimetric dehazing method.

Lane detection is crucial for driver assistance systems. However, road scenes are severely degraded in dense fog, which leads to the loss of robustness of many lane detection methods. For this problem, an end-to-end method combining polarimetric dehazing and lane detection is proposed in this paper. From images with dense fog captured by a vehicle-mounted monochrome polarization camera, the darkest and brightest images are synthesized. Then, the airlight degree of polarization is estimated from angle of polarization, and the airlight is optimized by guided filtering to facilitate lane detection. After dehazing, the lane detection is carried out by a Canny operator and Hough transform. Having helped achieve good lane detection results in dense fog, the proposed dehazing method is also adaptive and computationally efficient. In general, this paper provides a valuable reference for driving safety in dense fog.

Extrinsic Parameter Calibration Method for a Visual/Inertial Integrated System with a Predefined Mechanical Interface.

For a visual/inertial integrated system, the calibration of extrinsic parameters plays a crucial role in ensuring accurate navigation and measurement. In this work, a novel extrinsic parameter calibration method is developed based on the geometrical constraints in the object space and is implemented by manual swing. The camera and IMU frames are aligned to the system body frame, which is predefined by the mechanical interface. With a swinging motion, the fixed checkerboard provides constraints for calibrating the extrinsic parameters of the camera, whereas angular velocity and acceleration provides constraints for calibrating the extrinsic parameters of the IMU. We exploit the complementary nature of both the camera and IMU, of which the latter assists in the checkerboard corner detection and correction while the former suppresses the effects of IMU drift. The results of the calibration experiment reveal that the extrinsic parameter accuracy reaches 0.04° for each Euler angle and 0.15 mm for each position vector component (1σ).

Board-like Fused-Thiophene Liquid Crystals and their Benzene Analogs: Facile Synthesis, Self-Assembly, p-Type Semiconductivity, and Photoluminescence.

Fused-thiophene discotic liquid crystals were designed and easily synthesized by Suzuki coupling and FeCl3 oxidized tandem cyclodehydrogenation reactions, including homo- and cross-coupling reactions. The resulting hexagonal and rectangular columnar mesomorphic supramolecular structures formed were characterized by polarizing optical microscopy, differential scanning calorimetry, and small-angle X-ray scattering. The charge carrier transport properties in the mesophases of two of the synthesized fused-thiophene discogens were measured by transient photocurrent time-of-flight (TOF) technique, revealing fast hole transport values in the range of 10-3 to 10-2  cm2 V-1 s-1 , thus demonstrating potential applications in electronic devices. The luminescent sanidic mesogens, with different extended π-conjugated systems, also emit blue, green, or red light, with absolute photoluminescent quantum yields as high as 18 %.

A 6-DOF Navigation Method based on Iterative Closest Imaging Point Algorithm.

To achieve six degree-of-freedom autonomous navigation of an inboard spacecraft, a novel algorithm called iterative closest imaging point (ICIP) is proposed, which deals with the pose estimation problem of a vision navigation system (VNS). This paper introduces the basics of the ICIP algorithm, including mathematical model, algorithm architecture, and convergence theory. On this basis, a navigation method is proposed. This method realizes its initialization using a Gaussian mixture model-based Kalman filter, which simultaneously solves the 3D-to-2D point correspondences and the camera pose. The initial value sensitivity, computational efficiency, robustness, and accuracy of the proposed navigation method are discussed based on simulation results. A navigation experiment verifies that the proposed method works effectively. The three-axis Euler angle accuracy is within 0.19° (1σ), and the three-axis position accuracy is within 1.87 mm (1σ). The ICIP algorithm estimates the full-state pose by merely finding the closest point couples respectively form the images obtained by the VNS and predicted at an initial value. Then the optimized solution of the imaging model is iteratively calculated and the full-state pose is obtained. Benefiting from the absence of a requirement for feature matching, the proposed navigation method offers advantages of low computational complexity, favorable stability, and applicability in an extremely simple environment in comparison with conventional methods.

Real-time polarization imaging algorithm for camera-based polarization navigation sensors.

Biologically inspired polarization navigation is a promising approach due to its autonomous nature, high precision, and robustness. Many researchers have built point source-based and camera-based polarization navigation prototypes in recent years. Camera-based prototypes can benefit from their high spatial resolution but incur a heavy computation load. The pattern recognition algorithm in most polarization imaging algorithms involves several nonlinear calculations that impose a significant computation burden. In this paper, the polarization imaging and pattern recognition algorithms are optimized through reduction to several linear calculations by exploiting the orthogonality of the Stokes parameters without affecting precision according to the features of the solar meridian and the patterns of the polarized skylight. The algorithm contains a pattern recognition algorithm with a Hough transform as well as orientation measurement algorithms. The algorithm was loaded and run on a digital signal processing system to test its computational complexity. The test showed that the running time decreased to several tens of milliseconds from several thousand milliseconds. Through simulations and experiments, it was found that the algorithm can measure orientation without reducing precision. It can hence satisfy the practical demands of low computational load and high precision for use in embedded systems.

Error Analysis and Calibration Method of a Multiple Field-of-View Navigation System.

The Multiple Field-of-view Navigation System (MFNS) is a spacecraft subsystem built to realize the autonomous navigation of the Spacecraft Inside Tiangong Space Station. This paper introduces the basics of the MFNS, including its architecture, mathematical model and analysis, and numerical simulation of system errors. According to the performance requirement of the MFNS, the calibration of both intrinsic and extrinsic parameters of the system is assumed to be essential and pivotal. Hence, a novel method based on the geometrical constraints in object space, called checkerboard-fixed post-processing calibration (CPC), is proposed to solve the problem of simultaneously obtaining the intrinsic parameters of the cameras integrated in the MFNS and the transformation between the MFNS coordinate and the cameras' coordinates. This method utilizes a two-axis turntable and a prior alignment of the coordinates is needed. Theoretical derivation and practical operation of the CPC method are introduced. The calibration experiment results of the MFNS indicate that the extrinsic parameter accuracy of the CPC reaches 0.1° for each Euler angle and 0.6 mm for each position vector component (1σ). A navigation experiment verifies the calibration result and the performance of the MFNS. The MFNS is found to work properly, and the accuracy of the position vector components and Euler angle reaches 1.82 mm and 0.17° (1σ) respectively. The basic mechanism of the MFNS may be utilized as a reference for the design and analysis of multiple-camera systems. Moreover, the calibration method proposed has practical value for its convenience for use and potential for integration into a toolkit.

Real-time Imaging Orientation Determination System to Verify Imaging Polarization Navigation Algorithm.

Bio-inspired imaging polarization navigation which can provide navigation information and is capable of sensing polarization information has advantages of high-precision and anti-interference over polarization navigation sensors that use photodiodes. Although all types of imaging polarimeters exist, they may not qualify for the research on the imaging polarization navigation algorithm. To verify the algorithm, a real-time imaging orientation determination system was designed and implemented. Essential calibration procedures for the type of system that contained camera parameter calibration and the inconsistency of complementary metal oxide semiconductor calibration were discussed, designed, and implemented. Calibration results were used to undistort and rectify the multi-camera system. An orientation determination experiment was conducted. The results indicated that the system could acquire and compute the polarized skylight images throughout the calibrations and resolve orientation by the algorithm to verify in real-time. An orientation determination algorithm based on image processing was tested on the system. The performance and properties of the algorithm were evaluated. The rate of the algorithm was over 1 Hz, the error was over 0.313°, and the population standard deviation was 0.148° without any data filter.

Angle algorithm based on Hough transform for imaging polarization navigation sensor.

Polarization navigation is a promising orientation-determination method inspired by insects' foraging behavior that offers the advantages of autonomous and high precision. In this paper, using the solar meridian as an azimuth reference is proposed. The model of the distribution pattern of the polarized skylight projected onto an imaging sensor is analyzed. The sufficient features of the solar meridian are proven. According to these features, an angle algorithm for an imaging polarization navigation sensor based on a machine-vision algorithm is proposed. In consideration of noise in images, the relation between the measured angle and the noise in images is modeled. This model cannot only optimize the threshold tolerance R in the algorithm but also describe the effects of several primary factors that can affect the measuring precision. In the simulation test, the measurement accuracy was better than 0.34°. When the algorithm was tested on the polarization-detection system, the measurement accuracy was better than 0.37°.