MEMS gyroscopes are widely used in Internet of Things (IoT) products to achieve attitude control or combined inertial navigation. However, temperature is a key factor affecting the system stability and performances, therefore temperature compensation is very important. This paper proposes a novel narrow-band force rebalance control method based on a band pass filter (BPF) and temperature self compensation for a MEMS gyroscope. A three-dimensional adaptive filter demodulator and scalable fuzzy controller are utilized for the closed loop control of the drive mode. Besides, the BPF is used as a controller to achieve the narrow-band force rebalance control without modulation or demodulation. The center frequency of the BPF is adjusted in real time to match the sense-mode resonant frequency. Meanwhile, its gain is tuned based on the sense-mode quality factor. The real-time sense-mode resonant frequency, sense-mode quality factor, mode-matching voltage, and demodulation phase can be obtained with the polynomial fitting formulas and drive-mode resonant frequency. Experimental results demonstrate that over the full temperature range from -40°;C to 80°;C, the closed loop control systems of the mode-splitting and mode-matching gyroscopes without and with self compensation are very robust, and the bandwidth drifts are all less than 5Hz. For the mode-splitting gyroscope, the temperature drifts of the zero bias and scale factor are improved by a factor of 3 and 1.9 respectively. However, for the mode-matching gyroscope, the temperature drifts of the zero bias and scale factor are improved by a factor of 80 and 8 respectively. Thus, the proposed self-compensation method is effective and promising.

With the wide application of the Internet of Things technology, the hardware security has attracted more and more attention from users around the world. Hardware Trojan (HT) of integrated circuit (IC) has become a main security threat gradually. Therefore, HT detection is very significant. In this article, a HT automatic test system used for side-channel test combined logic test is constructed with a high-performance oscilloscope, FPGA chips, a NI digital acquisition card and LabVIEW software. Besides, the test flow chart and data processing method are depicted in detail. Spectral feature analysis combined principal component analysis is proposed for feature extraction. Fuzzy C-means clustering combined spectral energy analysis is put forward to distinguish the Trojan category from the golden category. Then Fusion distance (i.e. Mahalanobis distance combined Euclidean distance) is presented for the real-time HT recognition. A 128-bit AES cipher circuit and a 2-bit counter are applied as a golden circuit and a Trojan circuit, respectively. Experimental results demonstrate that the detection accuracy is 100% and the proposed detection method can easily achieve 0.1% HT detection sensitivity, which verifies that the detection method is feasible and effective.

With the rapid development of economy, science, and technology, the aging issues become more and more serious. People aged above 65 have a risk of 28%–35% to fall. Among them, bedside falls happen most frequently. Therefore, the capability to detect fall events of the elderly is very important. In this article, a novel noncontact fall detector based on a MEMS low-resolution infrared sensor and a low-cost radar sensor is developed to detect bedside fall. Besides, IR image processing algorithms based on the adaptive filter, successive approximation, double boundary scans, and mathematical morphology processing are proposed in detail. Partition processing algorithm is used to suppress the influence of residual or existed heat sources on the bed or ground. Then, the statistical features of the center, area, temperature and duration, as well as stable flag and fall action flag, are extracted for fall recognition. Finally, a three-layer radial basis function neural network is applied to distinguish the fall events from the nonfall events. Considering the influence factors of ambient temperature, brightness, gender, dressing, fall posture, fall location, and scenario, a total of 640 tests are conducted and 5-fold cross validation is used to evaluate the classification performance. Experimental results indicate that the averages of the recall, precision, F1-Score, and detection accuracy are measured to be 91.25%, 94.76%, 92.97%, and 93.13%, respectively, which demonstrates that the proposed fall detection method is effective. Besides, the detection accuracy decreases from 96.88% to 85.94% as the ambient temperature rises. Hence, this noncontact fall detector can be widely applied for bedside fall detection at home, which is low cost, nonwearable, unobtrusive, noninvasive, and privacy preserved.

A high-precision digital readout interface for a ±15g open-loop MEMS capacitive accelerometer is present in this paper. The differential capacitance resulting from input acceleration is picked up by a low-noise switch-capacitor (SC) charge sensitive amplifier (CSA) and further digitized by a 2nd-order Σ-Δ ADC after amplification. In order to reduce the nonlinearity of the open-loop accelerometer with high mechanical sensitivity, a digital nonlinearity calibration system is implemented on chip with a 320×8-bit embedded EEPROM for parameters storage. Newton-Raphson iteration algorithm is utilized for compensation parameter calculation, and serial processing as well as floatingpoint operation is used for hardware overhead reduction. The interface designed in a 0.35-μm 3.3V/14V embedded EEPROM CMOS process occupies 12.14 mm2and draws 11.1mA from a 3.3-V supply. The measured original nonlinearity of the accelerometer is 0.32%, while it is reduced to 0.084% after the compensation parameters are written into EEPROM. Moreover, the accelerometer system achieves a noise floor of 5.5μg/√Hz over a 200-Hz bandwidth and a bias instability (BI) of 5.13μg.

An interface for a ±400°/s open-loop split-mode MEMS vibratory gyroscope working under atmospheric pressure is present in this paper. Due to the high damping and low mechanical sensitivity of the sensing element, a high polarization voltage of 30V is used to boost the oscillation amplitude of the drive resonator, and a low-noise trans-impedance amplifier (TIA) is designed to reduce the noise contribution of interface. Moreover, the phase regulation of the drive channel is achieved by a phase locking loop (PLL) with 0.1° phase adjustment for sense synchronous demodulation, eliminating the dc error caused by the split-mode phase delay, and a novel switch-capacitor (SC) amplitude regulation scheme is proposed for noise and area reduction. The output of the sense channel is digitized by a 2nd-order Σ-Δ ADC and further processed by a 58th-order FIR filter and 3rd-order temperature compensation. The interface designed in a 0.18-μm 1.8V/5V CMOS process occupies 12.2 mm2including all the low-voltage (LV) functional blocks. The gyroscope system draws 5.4mA from a 5-V supply, and achieves a noise floor of 0.002/s/√Hz over a 200-Hz bandwidth and a bias instability (BI) of 6.4°/hr without packaging.

A novel fully-differential switched-capacitor interface using DC-blocking technique is presented for a ±30 g closed-loop capacitive micro-accelerometer. In view of the indispensable high-voltage feedback in a high-g large-mass closed-loop accelerometer resulting in a high power consumption, a charge sensitive amplifier with DC-blocking structure is utilized in the closed loop, separating the low-voltage sensing from high-voltage feedback and making most of loop modules work in the low-voltage domain. Moreover, owing to the DC-blocking structure, the switched-capacitor closed-loop system achieves a full-period feedback instead of the conventional time-multiplexing feedback, and the closed-loop system can therefore operate at a higher sampling frequency without increased working current, further reducing the aliasing noise. The interface designed in a 0.35 μm 3.3V/15V CMOS process occupies 9 mm2. The simulation results show that it consumes 12.77 mA from a 3.3-V supply and only 64.2 μA from a 15-V supply at a 1-MHz sampling clock, which is comparable to the power dissipation of low-g counterparts, and the dynamic range is 120.37 dB over a 200-Hz bandwidth.