Wide-Band Interference Mitigation in GNSS Receivers Using Sub-Band Automatic Gain Control

The performance of GNSS receivers is significantly affected by interference signals. For this reason, several research groups have proposed methods to mitigate the effect of different kinds of jammers. One effective method for wide-band IM is the HDDM PB. It provides good performance to pulsed and frequency sparse interference. However, it and many other methods have poor performance against wide-band noise signals, which are not frequency-sparse. This article proposes to include AGC in the HDDM structure to attenuate the signal instead of removing it: the HDDM-AGC. It overcomes the wide-band noise limitation for IM at the cost of limiting mitigation capability to other signals. Previous studies with this approach were limited to only measuring the CN0 performance of tracking, but this article extends the analysis to include the impact of the HDDM-AGC algorithm on the PVT solution. It allows an end-to-end evaluation and impact assessment of mitigation to a GNSS receiver. This study compares two commercial receivers: one high-end and one low-cost, with and without HDDM IM against laboratory-generated interference signals. The results show that the HDDM-AGC provides a PVT availability and precision comparable to high-end commercial receivers with integrated mitigation for most interference types. For pulse interferences, its performance is superior. Further, it is shown that degradation is minimized against wide-band noise interferences. Regarding low-cost receivers, the PVT availability can be increased up to 40% by applying an external HDDM-AGC.

A large gain variable range, high linearity, lownoise, low DC offset VGAs used in BD system

In this paper, a large gain variable range, high linearity, low noise, low DC offset VGAs with a simple gain-dB variable circuit are introduced. In the VGAs chain, the last and the first VGAs employ Bipolar transistors, to improve the linearity and noise characteristics. And the middle three stages VGAs employ MOS transistors. The whole circuitry is designed in 0.35um BiCMOS process, including variable gain amplifiers (VGAs) , fixed gain amplifiers , gain control and DC offset cancellation parts. The automatic gain control loop (AGC) provides a process independent gain variable range of 60dB (including 50dB gain-dB-linearity variable range), with a 200us loop lock time, the VGAs provide a 73dB largest gain, the THD is less than 1% at a 1V(P-P) output level; the equivalent output integral noise is 0.011v/√hz@20MHz bandwidth. The whole area is 1173um*494 um, and the power is 7.1mA at 3.3V signal supply voltage.

Communication system improvement with control performance based on link quality in wireless sensor actuator networks

<span lang="EN-US">New communication and networking paradigms started with wireless sensor actuator networks (WSANs) to introduce new applications. One of these is the automatic gain control system (AGC). It will enable a high degree of the decentralized and mobile control. In this study, neural networks (NN) with fuzzy logic (one of the techniques of artificial intelligence (AI)) is used to enhance the control performance depending on the link quality. The NN and fuzzy inference system (FIS) with Mamdani’s method used to build a model reference, adaptive controller, for recompensing for delay time packets losses, and improving the reliability of WSAN. Between 88.62% and 99.99%, validation data is obtained for the medium and high conditions of operation with the proposed algorithm. Experimental and simulation results show a promising approach.</span>

Error Performance of Subsampling Digital Power Estimation for Integrated Receivers

Estimation of signal power levels at the output of integrated receiver building blocks is a vital function as the block voltage or power gains are set based on sensed power levels to maintain constant levels at block outputs in the receiver chain. RF and IF level real-time gain settings are determined with Automatic Gain Control (AGC) loops. AGC loop circuit topologies are usually based on analog detection circuits. These analog power detection circuits are based on techniques such as envelope detection, and logarithmic amplification usually accompanied by severe accuracy issues such as Process, Voltage and Temperature (PVT) spreads preventing correct gain adjustments. Adopting a dominantly digital approach to detect the signal power would ensure a significant reduction in PVT spreads. This work presents a review of the subsampling digital power estimation to create low power digital power estimations alternative to analog methods. The simulations of the method are applied to an AM and a 64-QAM signal. Simulation results show that the power estimation error is within the acceptable level of [Formula: see text][Formula: see text]dB.

SFCW Radar with an Integrated Static Target Echo Cancellation System

Continuous Wave (CW) radars systems, especially air-coupled Ground-Penetrating Radar (GPR) or Through-Wall Imaging Radar (TWIR) systems, echo signals reflected from a stationary target with high energy, which may cause receiver saturation. Another effect caused by reflection of stationary targets is noticeable as background within a radargram. Nowadays, radar systems use automatic gain control to prevent receiver saturation. This paper proposes a method to remove stationary targets automatically from the received signal. The method was designed for a radar system with a moving platform, with an assumption that the distance between the surface and target is constant. The design is proposed of an SFCW radar with an integrated system for real-time multiple static target Echo Cancellation (EC). The proposed EC system removes the static target using active Integrated Circuit (IC) components, which generate the corresponding EC signal for each frequency step of the SFCW radar and sum it with the received echo signal. This has the main advantage of removing even multiple echoes at any distance, and excludes the need for a high-dynamic-range receiver. Additionally, the proposed system has minimal impact on the radar size and power consumption. Besides static target removal, the antenna coupling can be removed if the signal appears to be constant. The operating frequency was selected between 500 MHz and 2.5 GHz, due to the limitation of the used electronic components. The experimental results show that the simulated target’s echo using a cable with a known length could be suppressed to up to 38 dB. Experimental results using a moving radar platform and the real environment scenario with static and dynamic targets, show that the proposed EC system could achieve up to 20 dB attenuation of the static target. The system does not affect any other target of interest, which can even move at any distance during the measurement. Therefore, this could be a promising method for further compact implementation into SFCW radars, or any other radar type that generates CW single frequencies.

A real-time music detection method based on convolutional neural network using Mel-spectrogram and spectral flux

Audio processing, including speech enhancement system, improves speech intelligibility and quality in real-time communication (RTC) such as online meetings and online education. However, such processing, primarily noise suppression and automatic gain control, is harmful to music quality when the captured signal is music instead of speech. A music detector can solve the issue above by switching off the speech processing when the music is detected. In RTC scenarios, the music detector should be low-complexity and cover various situations, including different types of music, background noises, and other acoustical environments. In this paper, a real-time music detection method with low-computation complexity is proposed, based on a convolutional neural network (CNN) using Mel-spectrogram and spectral flux as input features. The proposed method achieves overall 90.63% accuracy under different music types (classical music, instruments solos, singing-songs, etc.), speech languages (English and Mandarin), and noise types. The proposed method is constructed on a lightweight CNN model with a small feature size, which guarantees real-time processing.

Increasing the accuracy of the automatic control system of unmanned aircraft under conditions of non-stationary interference

An approach to solving the problem of improving the accuracy of an automatic control system for unmanned aerial vehicles (UAVs) in conditions of non-stationary interference is considered. Such interference is caused by random changes in the noise of the measuring sensors, which are installed in the UAV, when changing the yaw, roll and flight altitude of the UAV due to restructuring or transformation of the operating mode of the propulsion system of the UAV. Non-stationary noises do not allow obtaining the maximum effect of applying the theory of optimal filtration based on the classical Kalman filter. The authors proposed a method of stabilizing sensor noise by using a noise automatic gain control circuit installed in front of the Kalman filter. For its quantitative assessment, a team of authors developed a computer model and carried out dynamic modeling based on test signals, which showed the applicability of the classical Kalman filter in non-stationary conditions and a decrease in the filtering errors of the automatic control system.

PLL-based nanoresonator driving IC with automatic parasitic capacitance cancellation and automatic gain control

This paper presents a phase-locked loop (PLL) based resonator driving integrated circuit (IC) with automatic parasitic capacitance cancellation and automatic gain control. The PLL consisting of a phase frequency detector (PFD), a loop filter, and a voltage-controlled oscillator (VCO) makes the driving frequency to be locked at the resonant frequency. The resonator is modeled by Butterworth–Van Dyke equivalent circuit model with motional resistance of 72.8 kΩ, capacitance of 6.19 fF, inductance of 79.4 mH, and parasitic parallel capacitance of 2.59 pF. To mitigate the magnitude and phase distortion in the resonator frequency response, it is necessary to compensate for the parasitic capacitance. The proposed automatic parasitic capacitance cancellation loop is operated in the open-loop mode. In the automatic parasitic capacitance cancellation phase, the outputs of the transimpedance amplifier (TIA) at the lower and higher frequency than the resonant frequency (VH and VL), are compared, and the programmable compensation capacitor array matches the VH and VL using binary-searched algorithm to cancel the parallel parasitic capacitance. The automatic gain control (AGC) loop keeps the oscillation at the suitable amplitude, and the AGC output can be used as a measurement of the motional resistance. The AGC loop is also digitally controlled. The proposed resonator driving IC is designed in a 0.18-μm bipolar complementary metal oxide semiconductor double-diffused metal oxide semiconductor (BCDMOS) process with an active area of 3.2 mm2. The simulated phase noise is −61.1 dBc/Hz at 1 kHz and the quality factor ( Q-factor) is 59,590.