Branched fluorine/adamantane PBO precursor (preFABPBO), synthesized via random co-condensation between 2,2-bis(3-amino-4-hydroxyphenyl)hexafluoro propane, 1,3-adamantanedicarbonyl dichloride, and trimesoyl chloride, is performed as interfacial compatibilizer, bisphenol A dicyanate ester (BADCy) resin as polymer matrix, and poly(p-phenylene-2,6-benzobisoxazole) (PBO) fibers as reinforcements to prepare PBO fibers/FABPBO-BADCy wave-transparent laminated composites by high temperature molding. The mechanical properties, wave-transparent performances, and heat resistances of PBO fibers/BADCy composites are simultaneously improved by the addition of preFABPBO. The interlaminar shear strength (ILSS) and flexural strength of PBO fibers/FABPBO-BADCy composites are 48.9 and 665.3 MPa, respectively, increased by 33.2% and 13.3% compared to those of PBO fibers/BADCy composites (36.7 and 587.4 MPa). The dielectric constant and dielectric loss values at 10 6 Hz are 2.53 and 0.003, respectively, lower than those of PBO fibers/BADCy composites (3.06 and 0.006), and the corresponding wave transmission efficiency is 94.8%, which also presents excellent stability over the wide temperature (25-200 °C ) and frequency range (10 3 -10 7 Hz and 8.2-12.4 GHz). Meanwhile, the heat resistance index and glass transition temperature are 229.9 °C and 247.5 °C , also better than those of PBO fibers/BADCy composites (229.6 °C and 247.1 °C ).

The attitude estimation system based on vision/inertial fusion is of vital importance and great urgency for unmanned ground vehicles (UGVs) in GNSS-challenged/denied environments. This paper aims to develop a fast vision/inertial fusion system to estimate attitude; which can provide attitude estimation for UGVs during long endurance. The core idea in this paper is to integrate the attitude estimated by continuous vision with the inertial pre-integration results based on optimization. Considering that the time-consuming nature of the classical methods comes from the optimization and maintenance of 3D feature points in the back-end optimization thread, the continuous vision section calculates the attitude by image matching without reconstructing the environment. To tackle the cumulative error of the continuous vision and inertial pre-integration, the prior attitude information is introduced for correction, which is measured and labeled by an off-line fusion of multi-sensors. Experiments with the open-source datasets and in road environments have been carried out, and the results show that the average attitude errors are 1.11° and 1.96°, respectively. The road test results demonstrate that the processing time per frame is 24 ms, which shows that the proposed system improves the computational efficiency.

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In the GNSS-challenged/denied environments, compared with other aided navigation systems, synthetic aperture radar- (SAR-) aided navigation systems can achieve all-weather, all-day, and global positioning. This paper is aimed at designing a reliable navigation system for the supersonic vehicle in the whole flight phase. Considering the SAR is of great significance for the reliable and precise navigation of the supersonic vehicle, we introduce it to the terminal phase to cope with the interference of the global navigation satellite system (GNSS). At the same time, to accelerate the speed of SAR positioning, a positioning method based on the area feature and stack sequential decoding algorithm (SSDA) is designed. Then, applying the SAR positioning under the framework of the Kalman filter (KF), we propose a tightly coupled strapdown inertial navigation system (SINS)/SAR/GNSS integration algorithm, which can achieve positioning without a complicated fusion method between the front phase and terminal phase. The flight experiment results show that the proposed method can correct the average position error to 1.7 m within 1 cycle.