Current Issue : April - June Volume : 2016 Issue Number : 2 Articles : 4 Articles
An attitude estimation algorithm is developed using an adaptive extended Kalman filter for low-cost micro tion algorithm is proposed\nfor fusing triaxial gyroscope and accelerometer measurements. An extended Kalman filter is implemented to estiate attitude in\ndirection cosine matrix (DCM) formation and to calibrate gyroscope biases online.We use a variable measurement covariance for\nacceleration measurements to ensure robustness against temporary non gravitational accelerations, which usually induce errors\nwhen estimating attitude with ordinary algorithms. The proposed algorithm enables accurate gyroscope online calibration by\nusing only a triaxial gyroscope and accelerometer. It outperforms comparable state-of-the-art algorithms in those cases when\nthere are either biases in the gyroscope measurements or large temporary non gravitational accelerations present. A low-cost,\ntemperature-based calibration method is also discussed for initially calibrating gyroscope and acceleration sensors. An open source\nimplementation of the algorithm is also available....
Examining the performance of the GNSS PLL, this paper presents novel results describing the statistical properties of four popular\nphase estimators under both strong- and weak-signal conditions when subject to thermal noise, deterministic dynamics, and typical\npedestrian motion. Design routines are developed which employ these results to enhance weak-signal performance of the PLL in\nterms of transient response, steady-state errors, and cycle-slips. By examining both single and data-pilot signals, it is shown that\nappropriate design and tuning of the PLL can significantly enhance tracking performance, in particular when used for pedestrian\napplications....
With modern global navigation satellite system (GNSS) signals, the FFT-based parallel code search acquisition must handle the\nfrequent sign transitions due to the data or the secondary code. There is a straightforward solution to this problem, which consists\nin doubling the length of the FFTs, leading to a significant increase of the complexity. The authors already proposed a method\nto reduce the complexity without impairing the probability of detection. In particular, this led to a 50% memory reduction for\nan FPGA implementation. In this paper, the authors propose another approach, namely, the splitting of a large FFT into three or\nfive smaller FFTs, providing better performances and higher flexibility. For an FPGA implementation, compared to the previously\nproposed approach, at the expense of a slight increase of the logic and multiplier resources, the splitting into three and five allows,\nrespectively, a reduction of 40% and 64% of the memory, and of 25% and 37.5% of the processing time.Moreover, with the splitting\ninto three FFTs, the algorithm is applicable for sampling frequencies up to 24.576MHz for L5 band signals, against 21.846MHz\nwith the previously proposed algorithm.The algorithm is applied here to the GPS L5 and Galileo E5a, E5b, and E1 signals....
We propose a motion planning gap-based algorithms for mobile robots in an unknown environment\nfor exploration purposes. The results are locally optimal and sufficient to navigate and explore\nthe environment. In contrast with the traditional roadmap-based algorithms, our proposed\nalgorithm is designed to use minimal sensory data instead of costly ones. Therefore, we adopt a\ndynamic data structure called Gap Navigation Trees (GNT), which keeps track of the depth discontinuities\n(gaps) of the local environment. It is incrementally constructed as the robot which navigates\nthe environment. Upon exploring the whole environment, the resulting final data structure\nexemplifies the roadmap required for further processing. To avoid infinite cycles, we propose to\nuse landmarks. Similar to traditional roadmap techniques, the resulting algorithm can serve key\napplications such as exploration and target finding. The simulation results endorse this conclusion.\nHowever, our solution is cost effective, when compared to traditional roadmap systems, which\nmakes it more attractive to use in some applications such as search and rescue in hazardous environments....
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