Robust Sparse Bayesian Two-Dimensional Direction-of-Arrival Estimation with Gain-Phase Errors.

To reduce the influence of gain-phase errors and improve the performance of direction-of-arrival (DOA) estimation, a robust sparse Bayesian two-dimensional (2D) DOA estimation method with gain-phase errors is proposed for L-shaped sensor arrays. The proposed method introduces an auxiliary angle to transform the 2D DOA estimation problem into two 1D angle estimation problems. A sparse representation model with gain-phase errors is constructed using the diagonal element vector of the cross-correlation covariance matrix of two submatrices of the L-shaped sensor array. The expectation maximization algorithm derives unknown parameter expression, which is used for iterative operations to obtain off-grid and signal precision. Using these parameters, a new spatial spectral function is constructed to estimate the auxiliary angle. The obtained auxiliary angle is substituted into a sparse representation model with gain and phase errors, and then the sparse Bayesian learning method is used to estimate the elevation angle of the incident signal. Finally, according to the relationship of the three angles, the azimuth angle can be estimated. The simulation results show that the proposed method can effectively realize the automatic matching of the azimuth and elevation angles of the incident signal, and improves the accuracy of DOA estimation and angular resolution.

Ultracompact single-layer optical MEMS accelerometer based on evanescent coupling through silicon nanowaveguides.

In this paper, a novel optical MEMS accelerometer is proposed based on evanescent coupling between parallel silicon nanowaveguides. The coupling length between nanowaveguides changes due to the input acceleration, leading to a great change of coupling efficiency. As a result, the applied acceleration can be obtained by measuring the transmission of waveguiding light. Simulation results with optical displacement sensing sensitivity of 32.83%/[Formula: see text]m within measurement range of 1.68 g is obtained. This design shows high compactness with no need of assembly, suggesting great potential in applications such as integrated photonic circuits.

High-precision micro-displacement sensor based on tunnel magneto-resistance effect.

A high-precision micro-displacement sensor based on tunnel magneto-resistance effect is reported.We designed and simulated magnetic characteristics of the sensor, and employed chip-level Au-In bonding to implement low-temperature assembly of the TMR devices. We employed the subdivision interpolation technique to enhance the resolution by translating the sine-cosine outputs of a TMR sensor into an output that varies linearly with the displacement. Simultaneously, using the multi-bridge circuit method to suppress external magnetic and geomagnetic interference. Experimental result shows that the micro-displacement sensor has a resolution of 800 nm, accuracy of 0.14[Formula: see text] and a full-scale range of up to millimeter level. This work enables a high-performance displacement sensor, and provides a significant guide for the design of a micro-displacement sensor in practical applications.