Narrowband image extraction is an essential preprocessing for multispectral imaging of filter array. This paper proposes an automatic method to extract narrowband images from a multispectral image. During offline phase, the method first employs horizontal and vertical projections to obtain initial positions of subsampling points. Then, integerpixel searching and half-pixel searching optimizes subsampling location. During on-line phase, 1:4 or 1:16 interpolation generates interpolation grids. Finally, four narrowband images are obtained according to the optimized subsampling points and interpolation grids. The experimental result indicates that this method effectively extracts narrowband images from originally mosaic images of multiple spectrums.
The integration of multiple Global Navigation Satellite Systems (GNSSs), such as the Chinese BeiDou Navigation Satellite System (BDS) and the American Global Positioning System (GPS), makes it possible to improve the accuracy of single-point positioning (SPP). However, the current accuracy of GNSS SPP with code measurement is on the order of several meters. In order to further improve SPP accuracy, we develop a multistep weighted least squares (MWLS) estimation method based on the elevation-dependent weighted least squares (EWLS) method. In this approach, the weight of each visible satellite is determined by its elevation and azimuth, and the coordinate components are semi-independently and separately calculated by MWLS. We conduct open-sky and blocked static tests as well as a vehicle-based kinematic test using single-frequency receivers to assess the effectiveness of this approach. Comparing the positioning errors of GPS and GPS/BDS SPPs between the MWLS and EWLS methods shows that the former improved the positioning accuracy more than the customary latter. Specifically, MWLS achieves a horizontal accuracy of about 1 m and a positional accuracy of 2 to 3 m in clear observational environments, about 15% better than ELWS.
Low-cost receivers have already entered the mass market over the past few years. The high-precision real-time kinematic and precise-point positioning evaluation based on low-cost receivers has been analyzed and verified by many other studies in the past. With the integration of the multiglobal navigation satellite system (GNSS) and advances in technology, low-cost GNSS receivers are expected to be widely used in vehicle navigation. To investigate the kinematic single-point positioning (SPP) performance of low-cost receivers, we first assembled a low-cost receiver that can receive both American global positioning system (GPS) L1 and Chinese BeiDou Navigation Satellite System (BDS) B1 signals simultaneously. Then, a vehicle-positioning experiment is conducted in Fuzhou, China. For comparison purposes, the assembled low-cost receiver and a higher-grade receiver are connected to a survey-grade antenna via a power divider. The positioning accuracy and position dilution of the precision of GPS, BDS, and GPD/BDS SPP with both receivers are compared and analyzed. The results indicate that the low-cost receiver can achieve horizontal precision better than 1 m in the combined GPS/BDS case, when the car is positioned in the urban main road and expressway. This result is competitive and similar to that of the higher-grade receiver. Moreover, although the positioning precision of the low-cost receiver is worse than that of the higher-grade receiver in the GPS-only and BDS-only SPP case, it outperforms the higher-grade receiver in terms of satellite tracking, especially for tracking GPS satellite.