Light-Activated Virtual Sensor Array with Machine Learning for Non-Invasive Diagnosis of Coronary Heart Disease

Early non-invasive diagnosis of coronary heart disease(CHD)is critical.However,it is challenging to achieve accurate CHD diagnosis via detecting breath.In this work,heterostructured complexes of black phosphorus(BP)and two-dimensional carbide and nitride(MXene)with high gas sensitivity and photo responsiveness were formulated using a self-assembly strategy.A light-activated virtual sensor array(LAVSA)based on BP/Ti_(3)C_(2)Tx was prepared under photomodulation and further assembled into an instant gas sensing platform(IGSP).In addition,a machine learning(ML)algorithm was introduced to help the IGSP detect and recognize the signals of breath samples to diagnose CHD.Due to the synergistic effect of BP and Ti_(3)C_(2)Tx as well as photo excitation,the synthesized heterostructured complexes exhibited higher performance than pristine Ti_(3)C_(2)Tx,with a response value 26%higher than that of pristine Ti_(3)C_(2)Tx.In addition,with the help of a pattern recognition algorithm,LAVSA successfully detected and identified 15 odor molecules affiliated with alcohols,ketones,aldehydes,esters,and acids.Meanwhile,with the assistance of ML,the IGSP achieved 69.2%accuracy in detecting the breath odor of 45 volunteers from healthy people and CHD patients.In conclusion,an immediate,low-cost,and accurate prototype was designed and fabricated for the noninvasive diagnosis of CHD,which provided a generalized solution for diagnosing other diseases and other more complex application scenarios.

An effective DOA method via virtual array transformation

A new DOA estimation method is presented for the virtual arraytransformation and the improved spatial smoothing algorithm. The new method not only overcomes the weakness of the ambiguity of DOA estimation of arbitrary array, but also improves the abilities of resolution and de-correlation. It is proven to be effective by theoretical analyses and computer simulations. What is more, the method can improve the estimation and resolution of DOA under the condition of sparse practical array.

NON-UNIFORM LINEAR ARRAY CONFIGURATION FOR MIMO RADAR

Array configuration of multiple-input multiple-output （MIMO） radar with non-uniform linear array （NLA） is proposed. Unlike a standard phased-array radar where NLA is used to generate thinner beam patterns, in MIMO radar the property of NLA is exploited to get more distinct virtual array elements so as to improve pa- rameter identifiability, which means the maximum number of targets that can be uniquely identified by the radar. A class of NLA called minimum redundancy linear array （MRLA） is employed and a new method to construct large MRLAs is descrihed. The numerical results verify that compared to uniform linear array （ULA） MIMO radars, NLA MIMO radars can retain the same parameter identifiability with fewer physical antennas and achieve larger aperture length and lower Cramer-Rao bound with the same number of the physical antennas.

High-resolution bottom detection algorithm for a multibeam echo-sounder system with a U-shaped array

High-resolution approaches such as multiple signal classification and estimation of signal parameters via rotational invariance techniques（ESPRIT） are currently employed widely in multibeam echo-sounder（MBES）systems for sea floor bathymetry,where a uniform line array is also required.However,due to the requirements in terms of the system coverage/resolution and installation space constraints,an MBES system usually employs a receiving array with a special shape,which means that high-resolution algorithms cannot be applied directly.In addition,the short-term stationary echo signals make it difficult to estimate the covariance matrix required by the high-resolution approaches,which further increases the complexity when applying the high-resolution algorithms in the MBES systems.The ESPRIT with multiple-angle subarray beamforming is employed to reduce the requirements in terms of the signal-to-noise ratio,number of snapshots,and computational effort.The simulations show that the new processing method can provide better fine-structure resolution.Then a highresolution bottom detection（HRBD） algorithm is developed by combining the new processing method with virtual array transformation.The application of the HRBD algorithm to a U-shaped array is also discuss.The computer simulations and experimental data processing results verify the effectiveness of the proposed algorithm.

Direction of arrival estimation of coherent sources based on arbitrary plane arrays

A method of direction of arrival (DOA) estimation of coherent sources is proposed, which is based on arbitrary plane arrays. After constructing the mathematical model of coherent sources, virtual array transformation and MUSIC algorithm are used to realize the azimuth estimation of coherent sources, which improved the DOA estimation performance greatly. According to the computer simulation, its validity is confirmed.

2D Augmented Coprime Array Geometry Based on the Difference and Sum Coarray Concept

The concept of difference and sum(diff-sum)coarray has attracted a lot of attentions in the estimation of direction-of-arrival(DOA)for the past few years,due to its high degrees-of-freedom(DOFs).A vectorized conjugate augmented MUSIC(VCA-MUSIC)algorithm is applied to generate an equivalent signal model which contains the virtual sensor positions of both the difference and sum of the physical sensors in the two-dimensional(2D)arrays,by utilizing both the spatial and temporal information.Besides,an augmented 2D coprime array configuration is presented with the basis on the concept of difference and sum coarray.By compressing the inter-element spacing of one subarray and introducing the proper separation between the two subarrays of 2D coprime array,the redundancy between the difference coarray and the sum one can be reduced so that more virtual sensors in both coarrays can make contributions to the DOFs.As a result,a much larger consecutive area in the diff-sum coarray can be achieved,which can significantly increase the DOFs.Numerical simulations verify the superiority of the proposed array configuration.

High-repetition-rate pulsed fiber laser based on virtually imaged phased array

High-repetition-rate(HRR) pulsed fiber lasers have attracted much attention in various fields. To effectively achieve HRR pulses in fiber lasers, dissipative four-wave-mixing mode-locking is a promising method. In this work, we demonstrated an HRR pulsed fiber laser based on a virtually imaged phased array(VIPA), serving as a comb filter. Due to the high spectral resolution and low polarization sensitivity features of VIPA, the 30 GHz pulse with high quality and high stability could be obtained. In the experiments, both the single-waveband and dual-waveband HRR pulses were achieved. Such an HRR pulsed fiber laser could have potential applications in related fields, such as optical communications.

PULSE CUMULATING METHOD FOR MULTI-TARGETS' JOINT AZIMUTH-ELEVATION FREQUENCY-DELAY ESTIMATION

The Directions of Arrivals （DOAs）, speeds and distances of targets are all required for array signal processing. Based on the periodic phase shift of coherent pulse sequence waveform, a new estimation of multi-targets＇ 2-Dimentional （2-D） DOA angle, Doppler frequency shift and relative time-delay is proposed. Based on a virtual sensor array constructed by pulse cumulating, the estinaations of azimuth, elevation, Doppler frequency shift and time-delay can be obtained simultaneously, and the least number of pulses could be two. This method is computationally efficient even in heavier noised environment, and all estimations are automatically paired in calculation process with no used to any plane sensor array and deal with many spectrum searching. Further more, this algorithm can be targets at the same time only by few sensors. The targets number that can deal with simultaneously is several times to the sensor number, which is the upper limit for normal algorithms such as ESPRIT and MUSIC. These characteristics would be very useful, especially, for aerial systems. Simulations demonstrate the capabilities of this method efficiently.

VIPA-based two-component detection for a coherent population trapping experiment

We demonstrate a two-component detection of a coherent population trapping(CPT)resonance based on virtually imaged phased array(VIPA).After passing through a VIPA,the two coupling lights with different frequencies in the CPT experiment are separated in space and detected individually.The asymmetric lineshape is observed experimentally in the CPT signal for each component,and the comparison with the conventional detection is presented.The shift of the CPT resonant frequency is studied with both the two-component and one-component detections.Our scheme provides a convenient way to further study the CPT phenomenon for each frequency component.