Design and Manufacture of Millimeter-Scale 3D Transformers for RF-IC.

The development of radio-frequency integrated circuits (RF-IC) necessitates higher requirements for the size of microtransformers. This paper describes millimeter-scale 3D transformers in millimeter-scale, solenoidal, and toroidal transformers manufactured using Micro-electromechanical Systems (MEMS). Two through-silicon via (TSV) copper coils with a high aspect ratio are precisely interleaved on a reserved air core (magnet core cavity) with a vertical height of over 1 mm because of the thickness of the substrate, which increases the performance while reducing the footprint. The effects of the wire width, coil turns, magnetic core, and substrate on the performance of the two transformers are discussed through numerical simulations. When an air core is present, solenoidal transformers are better than toroidal transformers in terms of performance and footprint; however, the gap decreases when the size is reduced. Additionally, the magnetic core significantly improves the performance of the toroidal transformer compared to that of the solenoid. Thus, the toroidal transformer has a higher potential for further size reduction. The two types of transformers were then manufactured completely using MEMS and electroplating. This paper discusses the influence of various parameters on millimeter-scale 3D transformers and realizes processing in silicon, which provides the foundation for integrating transformers in a chip.

Smartphone-Based Pedestrian Dead Reckoning for 3D Indoor Positioning.

Indoor localization based on pedestrian dead reckoning (PDR) is drawing more and more attention of researchers in location-based services (LBS). The demand for indoor localization has grown rapidly using a smartphone. This paper proposes a 3D indoor positioning method based on the micro-electro-mechanical systems (MEMS) sensors of the smartphone. A quaternion-based robust adaptive cubature Kalman filter (RACKF) algorithm is proposed to estimate the heading of pedestrians based on magnetic, angular rate, and gravity (MARG) sensors. Then, the pedestrian behavior patterns are distinguished by detecting the changes of pitch angle, total accelerometer and barometer values of the smartphone in the duration of effective step frequency. According to the geometric information of the building stairs, the step length of pedestrians and the height difference of each step can be obtained when pedestrians go up and downstairs. Combined with the differential barometric altimetry method, the optimal height can be computed by the robust adaptive Kalman filter (RAKF) algorithm. Moreover, the heading and step length of each step are optimized by the Kalman filter to reduce positioning error. In addition, based on the indoor map vector information, this paper proposes a heading calculation strategy of the 16-wind rose map to improve the pedestrian positioning accuracy and reduce the accumulation error. Pedestrian plane coordinates can be solved based on the Pedestrian Dead-Reckoning (PDR). Finally, combining pedestrian plane coordinates and height, the three-dimensional positioning coordinates of indoor pedestrians are obtained. The proposed algorithm is verified by actual measurement examples. The experimental verification was carried out in a multi-story indoor environment. The results show that the Root Mean Squared Error (RMSE) of location errors is 1.04-1.65 m by using the proposed algorithm for three participants. Furthermore, the RMSE of height estimation errors is 0.17-0.27 m for three participants, which meets the demand of personal intelligent user terminal for location service. Moreover, the height parameter enables users to perceive the floor information.

Study on Multi-GNSS Precise Point Positioning Performance with Adverse Effects of Satellite Signals on Android Smartphone.

The emergence of dual frequency global navigation satellite system (GNSS) chip actively promotes the progress of precise point positioning (PPP) technology in Android smartphones. However, some characteristics of GNSS signals on current smartphones still adversely affect the positioning accuracy of multi-GNSS PPP. In order to reduce the adverse effects on positioning, this paper takes Huawei Mate30 as the experimental object and presents the analysis of multi-GNSS observations from the aspects of carrier-to-noise ratio, cycle slip, gradual accumulation of phase error, and pseudorange residual. Accordingly, we establish a multi-GNSS PPP mathematical model that is more suitable for GNSS observations from a smartphone. The stochastic model is composed of GNSS step function variances depending on carrier-to-noise ratio, and the robust Kalman filter is applied to parameter estimation. The multi-GNSS experimental results show that the proposed PPP method can significantly reduce the effect of poor satellite signal quality on positioning accuracy. Compared with the conventional PPP model, the root mean square (RMS) of GPS/BeiDou (BDS)/GLONASS static PPP horizontal and vertical errors in the initial 10 min decreased by 23.71% and 62.06%, respectively, and the horizontal positioning accuracy reached 10 cm within 100 min. Meanwhile, the kinematic PPP maximum three-dimensional positioning error of GPS/BDS/GLONASS decreased from 16.543 to 10.317 m.

Intrinsic Identification and Mitigation of Multipath for Enhanced GNSS Positioning.

In global navigation satellite system (GNSS)-based positioning and applications, multipath is by far the most obstinate impact. To overcome paradoxical issues faced by current processing approaches for multipath, this paper employs an intrinsic method to identify and mitigate multipath based on empirical mode decomposition (EMD) and Hilbert-Huang transform (HHT). Frequency spectrum and power spectrum are comprehensively employed to identify and extract multipath from complex data series composed by combined GNSS observations. To systematically inspect the multipath from both code range and carrier phase, typical kinds of combinations of the GNSS observations including the code minus phase (CMP), differential correction (DC), and double differential (DD) carrier phase are selected for the suggested intrinsic approach to recognize and mitigate multipath under typical positioning modes. Compared with other current processing algorithms, the proposed methodology can deal with multipath under normal positioning modes without recourse to the conditions that satellite orbits are accurately repeated and surrounding environments of observing sites remain intact. The method can adaptively extract and eliminate multipath from solely the GNSS observations using intrinsic decomposition mechanism. From theoretical discussions and validating tests, it is found that both code and carrier phase multipath can be identified and distinguished from ionospheric delay and other impacts using the EMD based techniques. The resultant positioning accuracy is therefore improved to an obvious extent after the removal of the multipath. Overall, the proposed method can form an extensive and sound technical frame to enhance localization accuracy under typical GNSS positioning modes and harsh multipath environments.

Fabrication and Optimization of High Aspect Ratio Through-Silicon-Vias Electroplating for 3D Inductor.

In this study, the filling process of high aspect ratio through-silicon-vias (TSVs) under dense conditions using the electroplating method was efficiently achieved and optimized. Pulsed power was used as the experimental power source and the electroplating solution was prepared with various additive concentrations. Designed control variable experiments were conducted to determine the optimized method. In the control variable experiments, the relationship of multiple experimental variables, including current density (0.25⁻2 A/dm²), additive concentration (0.5⁻2 mL/L), and different shapes of TSVs (circle, oral, and square), were systematically analyzed. Considering the electroplating speed and quality, the influence of different factors on experimental results and the optimized parameters were determined. The results showed that increasing current density improved the electroplating speed but decreased the quality. Additives worked well, whereas their concentrations were controlled within a suitable range. The TSV shape also influenced the electroplating result. When the current density was 1.5 A/dm² and the additive concentration was 1 mL/L, the TSV filling was relatively better. With the optimized parameters, 500-µm-deep TSVs with a high aspect ratio of 10:1 were fully filled in 20 h, and the via density reached 70/mm². Finally, optimized parameters were adopted, and the electroplating of 1000-µm-deep TSVs with a diameter of 100 µm was completed in 45 h, which is the deepest and smallest through which a three-dimensional inductor has ever been successfully fabricated.