Performance comparison of high resolution bearing estimation algorithms using simulated and sea test data

1993 ◽  
Vol 18 (4) ◽  
pp. 438-446 ◽  
Author(s):  
A.K. Steele ◽  
C.L. Byrne ◽  
J.L. Riley ◽  
M. Swift
2014 ◽  
Vol 926-930 ◽  
pp. 1840-1845
Author(s):  
Hao Zhou ◽  
Zhi Jie Huo

This dissertation systematically studies beam space high resolution bearing estimation algorithms. The solution to target resolving and bearing estimation is proposed to remove the contribution from interferes outside the beam coverage area. MVDR adaptive beam based on sample covariance matrix inversion (SMI) is demonstrated for the condition under which strong interferes and signals are weakly correlated. For the situation that strong interferes and signals are strongly correlated, MVDR beam forming algorithm based on virtual interferes is proposed to suppress strong interferes. Simulation results indicate that the beam space MUSIC algorithm based on MVDR is an effective way to resolve multiple targets in small angle domain.


2021 ◽  
Vol 11 (5) ◽  
pp. 2318
Author(s):  
David Macii ◽  
Daniel Belega ◽  
Dario Petri

The Interpolated Discrete Fourier Transform (IpDFT) is one of the most popular algorithms for Phasor Measurement Units (PMUs), due to its quite low computational complexity and its good accuracy in various operating conditions. However, the basic IpDFT algorithm can be used also as a preliminary estimator of the amplitude, phase, frequency and rate of change of frequency of voltage or current AC waveforms at times synchronized to the Universal Coordinated Time (UTC). Indeed, another cascaded algorithm can be used to refine the waveform parameters estimation. In this context, the main novelty of this work is a fair and extensive performance comparison of three different state-of-the-art IpDFT-tuned estimation algorithms for PMUs. The three algorithms are: (i) the so-called corrected IpDFT (IpDFTc), which is conceived to compensate for the effect of both the image of the fundamental tone and second-order harmonic; (ii) a frequency-tuned version of the Taylor Weighted Least-Squares (TWLS) algorithm, and (iii) the frequency Down-Conversion and low-pass Filtering (DCF) technique described also in the IEEE/IEC Standard 60255-118-1:2018. The simulation results obtained in the P Class and M Class testing conditions specified in the same Standard show that the IpDFTc algorithm is generally preferable under the effect of steady-state disturbances. On the contrary, the tuned TWLS estimator is usually the best solution when dynamic changes of amplitude, phase or frequency occur. In transient conditions (i.e., under the effect of amplitude or phase steps), the IpDFTc and the tuned TWLS algorithms do not clearly outperform one another. The DCF approach generally returns the worst results. However, its actual performances heavily depend on the adopted low-pass filter.


2011 ◽  
Vol 5 (1) ◽  
Author(s):  
Ali Ranjbaran ◽  
Anwar Hasni Abu Hassan ◽  
Eng Swee Kheng

2015 ◽  
Vol 744-746 ◽  
pp. 1273-1276
Author(s):  
Ying Wei Cheng

The pavement performance study of bituminous mixture at surface course is very important. This paper focused on comparing the pavement performance of AC-l6C, AC-l6F, Super-12.5 and SMA-16 bituminous mixtures. First the gradations and material we used were illustrated. Then the dynamic stability, water stability and texture depth of these bituminous mixtures was tested. After comparing the test data, we found that the SMA-16 bituminous mixture has the best comprehensive pavement performance and it is most suitable for the surface layer bituminous mixture of freeways in Chinese Hubei Province. Super-12.5 and AC-l6C is applicable too, but AC-l6F is improper in this region.


2020 ◽  
Vol 12 (5) ◽  
pp. 765 ◽  
Author(s):  
Calimanut-Ionut Cira ◽  
Ramon Alcarria ◽  
Miguel-Ángel Manso-Callejo ◽  
Francisco Serradilla

Remote sensing imagery combined with deep learning strategies is often regarded as an ideal solution for interpreting scenes and monitoring infrastructures with remarkable performance levels. In addition, the road network plays an important part in transportation, and currently one of the main related challenges is detecting and monitoring the occurring changes in order to update the existent cartography. This task is challenging due to the nature of the object (continuous and often with no clearly defined borders) and the nature of remotely sensed images (noise, obstructions). In this paper, we propose a novel framework based on convolutional neural networks (CNNs) to classify secondary roads in high-resolution aerial orthoimages divided in tiles of 256 × 256 pixels. We will evaluate the framework’s performance on unseen test data and compare the results with those obtained by other popular CNNs trained from scratch.


Author(s):  
Wei Ma ◽  
Rongqi Wang ◽  
Xiaoqin Zhou ◽  
Guangwei Meng

Flexure hinges, which serve as the crucial joints in a large number of compliant mechanisms, have been widely applied in a variety of significant fields where there is high demand for the micro/nano motions with high resolution and high precision. Currently, an increasing number of notched flexure hinges with different structures and performances have been rapidly developed, but the existing performance comparisons on different notched flexure hinges were only conducted on seldom typical structures and are far from the comprehensiveness and fairness due to the different comparative conditions and discrepant evaluating indexes. Therefore, the finite beam-based matrix modeling method and nondimension precision factors will be employed in comprehensive comparing and ranking of 13 types of frequently-used notched flexure hinges in terms of their main compliances, motion accuracies, and stress concentrations, further providing useful practical guidelines to develop the compliant mechanisms with excellent overall performances.


Respirology ◽  
2014 ◽  
Vol 19 (4) ◽  
pp. 524-530 ◽  
Author(s):  
Daniela Gompelmann ◽  
Ralf Eberhardt ◽  
Dirk-Jan Slebos ◽  
Matthew S. Brown ◽  
Fereidoun Abtin ◽  
...  

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