As the commonly used wideband software radio receiver does not possess the performance of a high linear dynamic range under multiple signal excitation, a new type of adaptive wideband digital receiver architecture is proposed and designed based on blind nonlinear system identification. The traditional narrowband linear receiving and channelizing technologies should not be applied to deal with the complicated multiple-signal excitation with unknown or time-varying characteristics of time domain or frequency domain. Here, the harmonic and the intermodulation components brought about by the wideband digital receiver are firstly identified and extracted in the frequency domain, then a blind identification criterion for minimizing the short-time energy of the nonlinear components is designed, and the steepest descent method (SDM) or the recursive least square (RLS) algorithm is applied to extract and update iteratively the parameters of the nonlinear behavior model of the wideband digital receiver. Finally, the updated model is utilized to compensate the nonlinear distortion of the receiver in real time. The experimental results show that the spur-free dynamic range (SFDR) of the blind identification digital receiver achieves about 20-dB higher than that of the traditional receiver under multitone or 16-QAM bandpass signal excitation. As regards the large bandwidth and the high power efficiency of the RF front end and ADC circuits, the blind identification receiver architecture is helpful for detecting weak signal in concomitance with in-band or out-of-band strong jammers.

Gravitational wave (GW) detection is an important topic in fundamental scientific research. Studying high-precision capacitive displacement sensor (CDS) is crucial for capturing weak gravitational wave signals. However, existing research primarily focuses on noise analysis and optimization of the front-end and back-end circuits of CDS, with limited articles specifically studying the sensitive probe (SP). Therefore, this paper focuses on the modeling, analysis, and optimization of the SP in CDS. We establish a general model of the SP in COMSOL and extract the capacitance matrix to derive the displacement-capacitance curve between the displacement of each degree of freedom and the differential capacitance. By analyzing the capacitance matrix, we propose an equivalent circuit for the SP and verify its accuracy. Additionally, we optimize the structure of the SP and innovatively explore the impact of different electrode sizes on injection efficiency and induction efficiency. Overall, the works in this paper provide new perspectives for the design of high-precision CDS, and serve as a theoretical basis and reference for practical engineering design in GW detection.

A nuclear magnetic resonance (NMR) experiment for measurement of time-dependent magnetic fields was introduced. To improve the signal-to-interference-plus-noise ratio (SINR) of NMR data, a new method for interference cancellation and noise reduction (ICNR) based on singular value decomposition (SVD) was proposed. The singular values corresponding to the radio frequency interference (RFI) signal were identified in terms of the correlation between the FID data and the reference data, and then the RFI and noise were suppressed by setting the corresponding singular values to zero. The validity of the algorithm was verified by processing the measured NMR data. The results indicated that, this method has a significantly suppression of RFI and random noise, and can well preserve the FID signal. At present, the major limitation of the proposed SVD-based ICNR technique is that the threshold value for interference cancellation needs to be manually selected. Finally, the inversion waveform of the applied alternating magnetic field was given by fitting the processed experimental data.

The high precision multiple degree-of-freedom (DoF) capacitance sensor operating in milli-hertz band is critical for satellite platform inertial sensing of space gravitational wave detection mission, and the amplitude-phase characteristics inconsistency among the capacitive sensing channels may seriously deteriorate the displacement sensing performance. In this paper, a novel architecture of 6-DoF capacitive sensing circuits (CSCs) with digital quadrature demodulation is proposed, and the impact of 6-channel displacement sensing front-ends (DSFs) parameters inconsistency on the output signals and displacement sensing performance is also analyzed. The amplitude-phase inconsistency extraction and in-orbit in-situ calibration technique for the 6-channel capacitance sensor is proposed and verified by an invented ground-equivalent evaluation scheme. Finally, a 6-DoF CSCs prototype for the inertial sensors of “China TianQin Project” has been developed and tested. The results show the mean values and the standard deviations of the translational and rotational displacement detection errors are reduced from 1.32 μm, 5.67 mdeg to 30.86 nm, 86.92 μdeg, and from 18.22 nm, 76.51 μdeg to 12.23 nm, 32.97 μdeg, at the specific carrier frequency, respectively. The method may be utilized to periodically calibrate CSCs to significantly improve the prolonged in-orbit running performance of the inertial sensor.

Recently, nonlinear blind compensation technique has attracted growing attention in array signal processing application. However, due to the nonlinear distortion stemming from array receiver which consists of multi-channel radio frequency (RF) front-ends, it is too difficult to estimate the parameters of array signal accurately. A novel nonlinear blind compensation algorithm aims at the nonlinearity mitigation of array receiver and its spurious-free dynamic range (SFDR) improvement, which will be more precise to estimate the parameters of target signals such as their two-dimensional directions of arrival (2-D DOAs). Herein, the suggested method is designed as follows: the nonlinear model parameters of any channel of RF front-end are extracted to synchronously compensate the nonlinear distortion of the entire receiver. Furthermore, a verification experiment on the array signal from a uniform circular array (UCA) is adopted to testify the validity of our approach. The real-world experimental results show that the SFDR of the receiver is enhanced, leading to a significant improvement of the 2-D DOAs estimation performance for weak target signals. And these results demonstrate that our nonlinear blind compensation algorithm is effective to estimate the parameters of weak array signal in concomitance with strong jammers.

The cognitive radio wireless sensor network (CR-WSN) is experiencing more and more attention for its capacity to automatically extract broadband instantaneous radio environment information. Obtaining sufficient linearity and spurious-free dynamic range (SFDR) is a significant premise of guaranteeing sensing performance which, however, usually suffers from the nonlinear distortion coming from the broadband radio frequency (RF) front-end in the sensor node. Moreover, unlike other existing methods, the joint effect of non-constant group delay distortion and nonlinear distortion is discussed, and its corresponding solution is provided in this paper. After that, the nonlinearity mitigation architecture based on best delay searching is proposed. Finally, verification experiments, both on simulation signals and signals from real-world measurement, are conducted and discussed. The achieved results demonstrate that with best delay searching, nonlinear distortion can be alleviated significantly and, in this way, spectrum sensing performance is more reliable and accurate.