Vital signs are used as diagnostic parameters for monitoring medical and health conditions. This study proposes a distributed and non-contact multiple vital signs detection system based on dual-domain electromagnetic signals from microwave photonic ultra-wideband radar to measure respiratory and pulse rates of multiple individuals simultaneously. The proposed system is mainly composed an optical frequency operation module, a laser signal transmission and reception module, and a microwave signal transmission and reception module, utilizing ultra-wideband radiofrequency signals to achieve high-precision chest displacement measurements, while high-frequency optical signals enable accurate Doppler detection of pulse-induced micro-motions. The ultra-wideband transmitted signal enables the system to possess a high resolution of frequency, allowing precise discrimination of multiple individuals' vital signs in the frequency domain. In practical validation, the distributed system successfully accomplished simultaneous measurement of respiratory and pulse rates for two volunteers, demonstrating its multi-individual monitoring capability. The proposed distributed system is applicable to various scenarios such as hospitals, nursing homes, and home monitoring, demonstrating broad application prospects.

Delay jitter and dispersion are two important factors that impact the quality of radio over fiber transmission. In this paper, a simultaneous perception method for these two factors based on matched filtering is proposed. The proposed method effectively combines the precision of RF matched filtering process with the broadband advantages of microwave photonics technology, which can enable an accurate perception of both. The effectiveness of the proposed perception method is verified through experiments.

We present a dual-domain microwave photonic radar system for multi-parameter vital sign monitoring, utilizing ultra-wideband radiofrequency signals to achieve high-precision chest displacement measurements, while high-frequency optical signals enable accurate Doppler detection of pulse-induced micro-motions. We experimentally validated the system by simultaneously monitoring respiratory and pulse rate of two male volunteers, demonstrating high performance with average accuracies of 98.1

Microwave Photonics Inverse Synthetic Aperture Radar (MWP-ISAR) is an emerging imaging radar system that integrates photonics technology. By utilizing low-frequency ultra-wideband signals, MWP-ISAR achieves centimeter-level imaging precision for high-value targets. However, challenges persist when attempting to achieve high-precision imaging of maneuvering targets in airborne and maritime scenarios. Two main issues arise: (1) Non-cooperative target motion introduces 2-D spatial-variant phase errors in the echoes due to the high resolution. (2) Target maneuvering induces time-varying phase characteristics in the echoes. Existing autofocus and motion compensation algorithms struggle to address both spatial-variant and time-varying phase errors effectively. In this paper, a high-precision imaging algorithm for maneuvering targets is proposed, based on an improved Complex Variable Mode Decomposition (CVMD) approach. Firstly, the MWP-ISAR echo model for maneuvering targets is established, and the rationality and advantages of applying mode decomposition algorithms to ISAR imaging of maneuvering targets are investigated. In particular, the advantages of the CVMD method for resolution enhancement in small angle imaging. Subsequently, an ISAR imaging process is devised based on the CVMD algorithm. To enhance the performance of the CVMD algorithm and tackle the challenge of solving its parameters, a brute-force optimization algorithm is introduced. This strategy can effectively overcome the problem of difficulty in determining the decomposition mode number of the CVMD algorithm. Finally, high-resolution imaging of maneuvering targets at small turning angles was achieved. The effectiveness of the proposed algorithm is validated through multiple sets of simulation data and real MWP-ISAR data.

The accurate estimation of target scattering characteristics is deemed crucial in modern remote sensing technology, wherein valuable prior information is provided for radar applications, such as target recognition and auxiliary imaging. Ultra-wideband signals with high signal-to-noise ratios can be generated by microwave photonic radar (MWP), allowing for the precise estimation of target scattering characteristics. Due to the requirements of MWP radar in completing tasks, such as antiinterference and resource management, it usually emits radar signals in discrete subbands. However, discrete spectra lead to a significant reduction in the accuracy of target scattering parameter estimates. An algorithm that combines low-rank and sparse priors for the estimation of target attribute scattering parameters, along with the simultaneous recovery of the missing spectrum through a joint solution model, is introduced in this article. First, the impact of the missing spectrum on parameter estimation is analyzed by employing the MWP echo model with discrete subbands. Subsequently, a joint model for spectrum restoration and target parameter estimation, featuring low-rank and sparse priors, is constructed. An improved alternating direction method of multipliers algorithm is proposed for the joint solution of the problems related to missing spectrum recovery and scattering characteristics estimation. In contrast to traditional algorithms, the robustness of the optimization algorithm's solution is enhanced in this article through the introduction of an equilibrium threshold factor, thus preventing the global optimization problem from being trapped in local optima. Finally, the structural enhancement of imaging results by the estimated target scattering centers is demonstrated, thereby improving the interpretability of remote sensing images. The effectiveness of the algorithm proposed in this article is validated using measured MWP radar data.

A novel phase-coded microwave frequency comb generation method is proposed and experimentally demonstrated. The system is composed by a time domain mode locking (TDML) optoelectronic oscillator (OEO) and an external injection phase coding signal generator. When the period of the externally injected lower-frequency signal matches the delay time of the OEO loop, the TDML OEO can form a stable oscillation to generate a microwave frequency comb. By applying the phase coding period consistent with the round-trip delay time of the TDML OEO, a phase-coded microwave frequency comb is directly generated. Moreover, the central frequency of the phase coding signal is set to 0 Hz, resulting in the amplitude modulation of the microwave pulses. The magnitude of the phase-coded frequency comb signal is the amplitude modulation pulse signal.

Aiming at improving the performance of sparse aperture inverse synthetic aperture radar (ISAR) imaging under the condition of phase error, an efficient structural sparse imaging algorithm with joint phase autofocusing is proposed in this letter. First, an azimuth sparse ISAR imaging model containing phase error is constructed. To fully utilize the structural sparse characteristics of the imaging target, the above imaging model is further transformed into an $\boldsymbol {l}_{1}$ norm optimization problem using structural weighting. Second, leveraging fast iterative shrinkagethresholding algorithm (FISTA), the phase error estimation and the target structure weight updating are integrated into the image reconstruction framework. By solving this compound optimization problem iteratively, the final high-resolution ISAR imaging results are obtained. Finally, the experimental results of the measured data show that the proposed algorithm can achieve well-focused image efficiently under phase error conditions and has a remarkable imaging performance under low signal-to-noise ratio (SNR) and sparse aperture conditions due to the utilization of the sparse structure of the target.

The imaging of aerial targets using Inverse Synthetic Aperture Radar (ISAR) is affected by micro-Doppler effects resulting from localized micromotions, such as rotation and vibration. These effects introduce additional Doppler frequency modulation into the echo, leading to spectral broadening. Under ultrahigh-resolution conditions, these micromotions interfere with the focusing process of subject scatterers, resulting in images with poor focus showing significantly reduced quality. Furthermore, micro-Doppler signals exhibit temporal variability and nonstationary characteristics, posing difficulties in their estimation and differentiation from the echo. To address these challenges, this paper proposes a nonparametric method based on Variational Mode Decomposition (VMD) and mode optimization to separate the echo of the subject from micro-Doppler components. This separation is achieved by utilizing differences in their respective time-frequency distributions. This methodology mitigates the effect of micro-Doppler signals on the echo and obtains imaging results of a drone with ultrahigh-resolution. The VMD algorithm is introduced and subsequently extended to the complex domain. The method entails the decomposition of the ISAR echo along the azimuth direction into several mode functions distributed uniformly across the Doppler sampling bandwidth. Subsequently, image entropy indices are employed to optimize the decomposition parameters and select the imaging modes. This ensures the effective suppression of micro-Doppler signals and preservation of the subject echo. Compared to existing methods based on Empirical Mode Decomposition (EMD) and Local Mean Decomposition (LMD), the proposed method exhibits superior performance in suppressing image blurring caused by micro-Doppler effects while ensuring complete retention of fuselage details. Furthermore, the effectiveness and advantages of the proposed method are validated through simulations and processing of ultrawideband microwave photonic data obtained from drone measurements.

Microwave photonic technology has revolutionized conventional radar systems, enabling the imaging of critical components on non-cooperative airborne targets, such as engines and wings. However, the wide bandwidth and extensive rotation angle of Microwave Photonic Inverse Synthetic Aperture Radar (MWP-ISAR) pose significant challenges for achieving precise imaging. Specifically, correcting the spatially variant characteristics of the high-order components of range cell migration (RCM) in MWP-ISAR proves challenging. Additionally, variations in the scattering characteristics of different structural components introduce unknown component phase errors, further complicating existing imaging algorithms. To address these challenges in MWP-ISAR imaging, an innovative approach is introduced. The core of this algorithm lies in utilizing the energy trajectory of the echo to accurately estimate the motion parameters of non-cooperative target. The proposed method ensures high-precision correction of multi-order RCM through the reconstructed motion trajectory, concurrently extracting and compensating for unknown structural phase errors. The paper initially establishes the MWP-ISAR echo model, providing detailed insights into the trajectory reconstruction and multi-order RCM simultaneous correction algorithm. Despite the correction of RCM, residual unknown component phase errors in the echo continue to impact imaging quality significantly. To mitigate this, a phase compensation algorithm is introduced. Building on preliminary imaging results, a separation processing algorithm is devised to isolate echoes from each structural component. Subsequently, an autofocus algorithm is employed to precisely estimate phase errors for each structural component. Ultimately, the proposed method combines high-precision imaging results for all components, yielding a well-focused target image. The efficacy of the approach is substantiated through rigorous numerical simulations and real measurement data.

A multifunction processor for a broadband signal based on the active mode-locking optoelectronic oscillator (OEO) is proposed and experimentally demonstrated. The central frequency down-conversion and frequency spectrum convolution of the target broadband signal (TBS) are realized by just tuning the wavelength of the optical carrier or by the time domain product, respectively. To achieve the central frequency down-conversion of the TBS, an optical tunable delay line (OTDL) is adopted to match the delay time of the OEO loop with the repetition period of the TBS. Then the spectrum convolution of the TBS is produced by just injecting a lower frequency signal consistent with the free spectral range (FSR) of the OEO loop. Moreover, the frequency convolution repetition is also greatly increased by harmonic mode-locking injection. The equivalent bandwidth of the TBS is enlarged by ∼50 times, benefiting from the frequency convolution. The central frequency conversion flexibility and the bandwidth compatibility are also discussed in detail. This work provides a multifunction processor system and may have potential usage in multifunctional integrated radar systems.

In this article, a broadband frequency measurement system based on optical spectrum manipulation and stimulated Brillouin scattering (SBS) is proposed and experimentally demonstrated, which can implement wide-range and high-resolution frequency measurement, and generate corresponding broadband interference signals in some frequency bands, that is, it has versatility. Since the frequency range of the pump light to excite SBS is expanded based on the optical spectrum manipulation and high resolution is ensured by the narrow scattering spectrum of SBS, high-resolution spectrum measurement covering a wide frequency band is finally implemented. In addition, the double sideband pump light can be used as the source of electronic interference signal. In the experiments, the frequency measurement range of the proposed system is tested to be 0.03–44 GHz, and the resolution is up to 3 MHz. Furthermore, the frequency measurement and electronic interference sharing the same work band can be carried out in the ranges of 6.3367–7.8367 GHz and 20.36–22.16 GHz.

Compared with conventional microwave regime radars, microwave photonic (MWP) radar is capable of transmitting extremely large bandwidth signals, wherein the frequencies of such signals distribute across multiple bands. In practical applications, the large bandwidth of MWP radar may be split into multiple discrete subbands due to various considerations such as antijamming, resource-saving, and communication band avoidance. Nonetheless, it leads to the fact that MWP radar suffers from the challenging problems of sidelobes' elevation and main lobes' broadening. These problems will affect the image quality seriously. To address this issue, a spectrum recovery algorithm based on an improved truncated Schatten-p norm and sparse regularizer-alternating direction method of multipliers (TSPN-ADMM) network is proposed in this article. This algorithm can efficiently recover the lost spectrum in MWP radar applications and further improve the imaging quality of the MWP radar. In the lost spectrum recovery problem, the parameters of the recovery algorithm directly determine the recovery performance. The different forms of lost spectrum possessed by MWP radar make the selection of parameters for the spectrum recovery algorithm extremely difficult. As a consequence, in this article, the spectrum recovery problem for MWP radar can be reformulated into a matrix completion problem by exploiting its joint sparsity and low-rankness. Based on the traditional TSPN-ADMM algorithm, an improved TSPN-ADMM-Net approach is proposed using the algorithm unrolling technique, wherein the hyperparameters in the TSPN-ADMM algorithm are optimized in an end-to-end training manner. Consequently, the algorithm proposed in this article can achieve excellent recovery results when dealing with the multiple spectrum missing situations existing in MWP radar. The effectiveness of the algorithm is verified by a combination of numerical simulations and actual MWP radar data.

A novel dual-domain mode-locked optoelectronic oscillator (DDML-OEO) is proposed and demonstrated to generate multi-carrier broadband signal. The DDML-OEO is built up by mode-locking a conventional OEO at the time domain and Fourier domain mutually. The Fourier domain mode locking (FDML) is achieved by driving the laser with a period triangular waveform voltage, of which the frequency is synchronized with the round-trip time of the OEO loop. Meanwhile, an electrical signal synchronizing with the free spectrum range (FSR) of the OEO loop is injected to realize the time domain mode locking (TDML) process. Through combined mechanisms of the FDML and TDML, the multi-carrier broadband signal can be directly generated via the DDML-OEO. Thanks to the TDML, different multi-carrier bands of the signal are coherent and the phase noise of the generated broadband waveform is strongly suppressed compared with free-running FDML-OEO. With the proposed scheme, an ultra-low phase noise of -111.1 dBc/Hz at 10 kHz offset for the generated multi-broadband signal waveform is achieved when the cavity length is about 3000 m. The bands interval, the bandwidth and the central frequency tunability are all discussed, which have great potential usage in multi-channel radar transmitter.

Compressive sensing (CS)-based methods have been widely used for sparse inverse synthetic aperture radar (ISAR) imaging. However, many CS-based methods are sensitive to the selection of model parameters, and the residual phase error of the echo also causes trouble for imaging and autofocusing. To address these problems, a novel deep learning approach, named as 2-D-IADIANet, is proposed to achieve 2-D sparse ISAR imaging with 2-D phase error estimation in this article. First, a 2-D ISAR sparse echo model with 2-D phase error into account is established, and a 2-D alternating direction method of multipliers (2-D-ADMM) frame-work-based method, dubbed as 2-D-IADIA, is presented to solve this compound reconstruction problem. Second, a 2-D-IADIA is further unfolded and mapped into a deep network form by integrating with a 2-D phase error compensation network. Moreover, all adjustable parameters can be learned adaptively by training the network through a back propagation algorithm in a complex domain directly. Finally, experimental results verify that the well-learned 2-D-IADIANet, which is only trained by a small amount of simulation samples, can also be generalized to measured data application. Especially, owing to the good performance of the network, the proposal has a superior reconstruction performance than 2-D-IADIA under the low 2-D sample rate and/or signal-to-noise ratio scenarios.

A microwave photonic (MWP) pulse radar system for high-resolution target detection is proposed and experimentally demonstrated in this article. In the transmitter, a pulsed linearly-frequency-modulated (LFM) wave is generated based on optical frequency operation module (OFOM), which can generate LFM waves with ultra-flexibly tunable center frequency. In the receiver, optical-domain down-conversion is employed to convert the incoming echo to an intermediate frequency signal by a microwave photonic frequency mixer, which can free the receiver from high-speed ADC and provide an excellent wideband processing. Experimentally, a Ku-band pulsed LFM wave with a bandwidth of 840 MHz is generated and received through self-closed-loop and target detection test by the constructed system. The performance verifies that the proposed pulsed MWP radar has the potential of supporting high-resolution detection and recognition of distant targets.

An optoelectronic oscillation method with reconfigurable multiple formats for simultaneous generation of coherent dual-band signals is proposed and experimentally demonstrated. By introducing a compatible filtering mechanism based on stimulated Brillouin scattering (SBS) effect into a typical Phase-shifted grating Bragg fiber (PS-FBG) notch filtering cavity, dual mode-selection mechanisms which have independent frequency and time tuning mechanism can be constructed. By regulating three controllers, the proposed scheme can work in different states, named mode 1, mode 2 and mode 3. At mode 1 state, a dual single-frequency hopping signals is achieved with 50 ns hopping speed and flexible central frequency and pulse duration ratio. The mode 2 state is realized by applying the Fourier domain mode-locked (FDML) technology into the proposed optoelectrical oscillator, in which dual coherent pulsed single-frequency signal and broadband signal is generated simultaneously. The adjustability of the time duration of the single-frequency signal and the bandwidth of the broadband signal are shown and discussed. The mode 3 state is a dual broadband signal generator which is realized by injecting a triangular wave into the signal laser. The detection performance of the generated broadband signals has also been evaluated by the pulse compression and the phase noise figure. The proposed method may provide a multifunctional radar system signal generator based on the simply external controllers, which can realize low-phase-noise or multifunctional detection with high resolution imaging ability, especially in a complex interference environment.

With the rapid development of microwave photonic technology in recent years, microwave photonic radar can generate and process signals far beyond the relative bandwidth of traditional radar, and can achieve centimeter-level resolution when imaging. However, the echo characteristics of microwave photonic radar are quite different from those of traditional radar, which degrades the performance of traditional imaging algorithms. Therefore, it is crucial to propose an imaging algorithm that is compatible with the characteristics of microwave photonic imaging radars. This paper first summarizes the development of microwave photonic imaging radar. Then analyzes the typical problems in the imaging process of microwave photonic radar, and proposes corresponding solutions to these problems. Finally the processing results of some measured data of microwave photonic imaging radar are shown.

A coherent dual-band microwave photonic (MWP) radar system is proposed and experimentally demonstrated in this paper. In the transmitter, coherent dual band linear frequency modulation (LFM) waves with the characteristics of tunable central frequency and the same large bandwidth are generated based on an improved optical frequency operation module (OFOM). In the receiver, the information of targets is obtained after the echoes at two bands are received and de-chirp processed simultaneously. Experimentally, the presented coherent dual-band MWP radar system operating in X band and Ku band with an instantaneous bandwidth of 3GHz is constructed. A target-detection experiment verifies that centimeter level resolution can be achieved by the system.

为切实提升预警人才培养质量、适应学员岗位任职需求,基于雷达原理与技术课程实战化教学存在问题,给出了课程实战化教学基本原则;对教学设计的各环节进行实战化赋能,提出了对策措施.教学实践表明,学员对雷达原理与技术课程实战化教学满意度较高,课程教学效益有一定提升.