KEYWORDS: Satellites, Particle swarm optimization, Particles, Error analysis, Evolutionary algorithms, Search and rescue, Time metrology, Computer simulations, Monte Carlo methods, Analytical research
In response to the existing beacon positioning methods in medium Earth orbit (MEO) search and rescue operations, an improved particle swarm optimization algorithm based on Time Difference of Arrival (TDOA) localization is proposed. The study analyzes and simulates the Geometric Dilution of Precision (GDOP) for TDOA localization, demonstrating that GDOP is directly proportional to time measurement errors and satellite position errors. Furthermore, a modified particle swarm optimization algorithm is presented, which incorporates an adaptive fitness function and adaptive parameter adjustments using a classic particle swarm optimization approach. The proposed method improves the inertial weight and introduces adaptive algorithms for fitness functions and inertial parameters. This improved particle swarm optimization algorithm not only effectively addresses issues such as poor convergence and susceptibility to local optima but also accurately determines the position of the beacon. Simulation results indicate that When the time error is 1μs, the improved Particle Swarm Optimization (PSO) algorithm achieves a positioning accuracy of 0.57km. This represents a 5% improvement over the classical PSO algorithm and a significant 15% improvement compared to the Weighted Least Squares (WLS) algorithm.
The GNSS-R approach improves altimetry, which is essential for maritime remote sensing data. High-precision altimetry requires carrier phase continuity, which is limited by several variables. This paper offered a grey model solution. The proposed method works for GNSS-R sea surface height measuring with centimeter-level accuracy. Field experiments process BeiDou satellite reflected signals in the B1 and B3 frequency bands, and GEO and IGSO inversion findings are analyzed. This method improves the GEO inversion effect, the satellite with a large altitude angle, and sea surface altimetry when comparing B1 and B3.
Surface elevation is one of the importance information for GIS. Usually surface elevation can acquired from many sources such as satellite imageries, aerial photograph, SAR data or LiDAR by photogrammetry, remote sensing methodology. However the most trust information describe the actual surface elevation is Leveling from terrestrial survey. Leveling is giving the highest accuracy but in the other hand is also long period process spending a lot of budget and resources, moreover the LiDAR technology is new era to measure surface elevation. ICESat/GLAS is spaceborne LiDAR platform, a scientific satellite lunched by NASA in 2003. The study area was located at the middle part of Thailand between 12. ° - 14° North and 98° -100° East Latitude and Longitude. The main idea is to compare and evaluate about elevation between ICESat/GLAS Altimetry and mean sea level of Thailand. Data are collected from various sources, including the ICESat/GLAS altimetry data product from NASA, mean sea level from Royal Thai Survey Department (RTSD). For methodology, is to transform ICESat GLA14 from TOPX/Poseidon-Jason ellipsoid to WGS84 ellipsoid. In addition, ICESat/GLAS altimetry that extracted form centroid of laser footprint and mean sea level were compared and evaluated by 1st Layer National Vertical Reference Network. The result is shown that generally the range of elevation between ICESat/GLAS and mean sea level is wildly from 0. 8 to 25 meters in study area.
KEYWORDS: Optical correlators, Digital signal processing, Signal processing, Modulation, Field programmable gate arrays, Detection and tracking algorithms, Global Positioning System, Sensors, Receivers, Satellite navigation systems
BOC signal structure was introduced in this paper. BOC signal modulation and BOC(1,1) auto-correlation function were analyzed in detail. Based on the signal acquisition, tracking loop for BOC(1,1), a hardware design with FPGA chip was presented for the correlator, implemented using EP2S60 from Altera Co. The hardware correlator architecture and functions were described with two key modules, i.e. Pseudo-Random Noise (PRN) code generator and Numerical Control Oscillator(NCO). The practical test results show that the designed hardware correlator can work steadily and correctly, which is valid for the BOC(1,1) signal acquisition and tracking.
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