Small-Range High-Precision Positioning Based on Two-Point Coordination for Robot

This paper proposed a two-point coordinated positioning algorithm. Based on the assumption that the distance between two points was constant, a fusion algorithm was introduced into the positioning process to enhance the positioning accuracy. The simulation results showed that the proposed algorithm could reduce the RMS error to about 50% of the improved sinc interpolation-based positioning algorithm when the sampling frequency was 500 MHz and the interpolation number was 19.

Extended use of receiver groups: Theory, synthetic example, and noise considerations

Receiver grouping is commonly used in marine towed-streamer seismic acquisition. Measurements from several receivers in a group are stacked to increase the signal-to-noise ratio of the resulting data and form an analog spatial antialiasing filter. I propose a method for extracting inline derivatives of the wavefield as additional measurements from the groups. This is achieved by multiplying the signal from the individual receivers in a group with predefined weights that corresponds to a finite-difference (FD) operator. The inline derivative(s) makes it possible to use multichannel sampling theorems to reconstruct the signal on a denser grid. Extraction of FD data from clusters of receivers is not a new concept, but I find that, by using the geometry of conventional streamer groups, it is possible to obtain FD data which are well suited for multichannel interpolation. The key to finding suitable FD operators is to recognize that it is not the ideal differentiation response we seek, but the impulse response of the group multiplied with the ideal differentiation response. Furthermore, under a Gaussian noise assumption, I derive formulas for the resulting noise level from sinc and higher order sinc interpolations. I find that the random noise level in the reconstructed data, when using higher order sinc interpolation, is expected to be higher than when using conventional sinc interpolation and will vary with respect to the distance from the original sampling points. The statistical analysis shows that it is beneficial to find FD operators with as small an [Formula: see text] norm as possible. A synthetic example shows that the proposed method of extracting FD operators and subsequent interpolation works very well. I foresee that the proposed method can be used to reduce the density of receivers (hydrophones or geophones) when designing new streamers or with existing equipment to improve the inline sampling.

An Improved Imaging Algorithm for High-Resolution Spotlight SAR with Continuous PRI Variation Based on Modified Sinc Interpolation

This paper focuses on an improved imaging algorithm for spotlight synthetic aperture radar (SAR) with continuous Pulse Repetition Interval (PRI) variation in extremely high-resolution. Conventional SAR systems are limited in that a wide swath cannot be achieved with a high azimuth resolution in the meantime. This limitation can be overcome by Pulse Repetition Frequency (PRF) variation in a SAR system. However, there are problems such as the ambiguities of point targets or extended targets caused by nonuniform sampling. A reconstructive method, Nonuniform Discrete Fourier Transform (NUDFT) has been presented in the current literature, but it is rather computationally expensive. In this paper, a modified sinc interpolation based on NUDFT is proposed, which is used to reconstruct the uniformly sampled echo in time domain. Since the interpolation kernel length is relatively short, it is more computationally efficient. Then, the two-step processing approach combined with the modified sinc interpolation is further presented, which has much better accuracy than that combined with the conventional sinc interpolation. Both the simulated data and the extracted GF-3 data experiment demonstrate the validity and accuracy of the proposed approach.

Vector Field Convolution-Based B-Spline Deformation Model for 3D Segmentation of Cartilage in MRI

In this paper, a novel 3D vector field convolution (VFC)-based B-spline deformation model is proposed for accurate and robust cartilage segmentation. Firstly, the anisotropic diffusion method is utilized for noise reduction, and the Sinc interpolation method is employed for resampling. Then, to extract the rough cartilage, features derived from