Optical wavelength measurement is imperative in a wide range of applications, such as optical metrology, sensing, wireless communication, and so on. In this paper, we propose and demonstrate a novel microwave photonic optical wavelength measurement method based on swept wavelength-to-time mapping, where the optical wavelength is mapped to the time domain information of a microwave photonic link with the help of a swept signal. Wavelength of the optical signal under test can therefore be measured by simply measuring the time domain information. To achieve swept wavelength-to-time mapping, a bi-directional frequency-swept optical signal for reference is first constructed. The reference optical signal and the optical signal under test is then combined and launched into a photodetector for optical-to-electrical conversion. A pair of microwave pulses can be observed, which is obtained by filtering the recovered photocurrent using an electrical bandpass filter with narrow passband. The occurrence time of the filtered pulses are related to the optical wavelength under test due to the bi-directional frequency-scanning property of the reference optical signal, thus swept wavelength-to-time mapping is enabled. Only a low-speed oscilloscope is needed for optical wavelength measurement by monitoring the time-domain information of the microwave pulses in the proposed method, which provides a cost-effective approach for microwave photonic optical wavelength measurement.
Microwave photonic signal processing such as microwave frequency measurement and temperature sensing has been widely studied due to its advantages such as large instantaneous bandwidth, high resolution, flexible reconfigurability as well as immunity to electromagnetic interference. In this paper, we review our recent works about microwave photonic signal processing based on parameter-to-time mapping, where the parameters under test, such as the frequency or temperature, are mapped to the time interval of the output pulses. Parameter-to-time mapping relationship is therefore established, and the parameter can be measured by using a low-speed time-domain acquisition equipment. The microwave photonic signal processing schemes based on parameter-to-time mapping feature low-cost and high resolution, which have great potential in applications such as radar, electronic warfare and metrology systems.
Mode matching has proven effective in suppressing the mode hopping in external cavity diode lasers (ECDLs) without antireflection coating. However, prolonged operation of ECDLs is susceptible to mode hopping induced by fluctuations in the equivalent internal cavity length. In this study, we introduce a rapid mode hopping identification method by monitoring the first derivative of the frequency scanning interference signal. Subsequently, an adaptive mode hopping suppression method, based on the acquisition of a priori knowledge for the initial current traversal optimization range, is applied to ECDLs. The experimental results demonstrate a significant extension in the stable operation time of the ECDL by a factor of 17, surpassing 7 h using the proposed rapid adaptive mode hopping suppression method.
In the field of machine vision, algorithms for estimating optical flow in sequential images have been proposed for many years. However, due to the advancements in image resolution and video frame rates of sensor, the optical flow algorithm running on a CPU or a GPU may struggle to meet real-time processing and low power consumption requirements. This paper presents an FPGA-based accelerated method for high-speed LK optical flow estimation. We implemented a serial input and multi-window output buffer structure to enhance the algorithm's parallel processing capability and improve processing speed. Additionally, we designed a multi-clock convolution structure to reduce resource consumption. Tested on the Middlebury dataset, the FPGA-based LK optical flow algorithm developed in this paper can achieve a processing speed of 330 frames per second for image sequences with a resolution of 640x480. It also maintains a relatively high level of accuracy and has low power consumption.
Spectral imaging is an imaging technique that introduces spectral filters in the imaging link to simultaneously obtain target spectral and spatial information. Among the spectral filters, liquid-crystal (LC) filters exhibit technical advantages of fast response speed, low power consumption, and large aperture. As a highly efficient electrically tunable microcavity interference filter structure, the miniaturized liquid-crystal Fabry-Pérot (LC-FP) is generally composed of a LC layer sandwiched by two highly reflective mirrors. By adjusting the applied voltage signals, the high spectral resolution spectrum selection and adjustment of transmitted beam is implemented. Generally, the birefringence difference of the LC material used determines the phase modulation capability, which in turn affects the device performance. In this paper, an electrically tunable LC-FP filter (ET LC-FP) with high-birefringence nematic LC mixture is proposed. The deviced ET LC-FP is constructed using a kind of high-birefringence nematic LC mixture (HB-45800) for achieving the typical electrically selecting and adjusting and jumping of spectral lightbeam outfrom the ET LC-FP filter. The electro-optical parameters of HB-45800 are: Δn = 0.385 at 589.3nm, the clear point is 95.1℃. The transmission spectral characteristics (1.5~15μm) of the ET LC-FP device were analyzed using a Fourier transform infrared spectrometer. Experiments demonstrate that an electrically tunable spectral resolution of better than 5nm is reached in the infrared domain of 1.5~3μm.
Microwave photonic technology has advantages of large bandwidth, high frequency, flexible reconfigurability and immunity to electromagnetic interference, which is widely used for the generation and processing of microwave signals. In this paper, we review our recent works about microwave signal generation and processing based on optical domain controlling, including photonic generation of multi-band and multi-format microwave waveforms, and microwave photonic temperature interrogation based on temperature-to-time mapping. The proposed works have great potential in practical applications, such as radar, measurement as well as sensing.
With the principle of electrically controlled birefringence (ECB), we propose a new method to spatially separate the azimuthally and radially polarized beams. The method is premised on a regularized arrangement of liquid-crystal (LC) induced by sparse polymer ribbons.The ECB effect was achieved by a hole-patterned LC device with an initial radial alignment, which is induced by polymer ribbons pre-fabricated on the substrate. The polymer ribbons were formed on the substrate via the ultraviolet (UV) mask exposure method, which has the advantages of low cost, simple fabrication process and can be used for mass production. When the voltage signals are applied to the fabricated LC device, a gradient refractive index distribution will form inside the device. Restricted by the inherent polarization-sensitive properties of the nematic phase, it corresponds to the extraordinary optical component, which is exactly the radially polarized beam. According to the above principle, the extraordinary and ordinary polarized components can be separated. Experiments demonstrated that the spatial separation was effectively achieved by the proposed LC device. The proposed method has provided an approach for the light field manipulation based on patterned liquid crystal alignment.
The star sensor is an attitude-sensitive device for spaceflight. It is a critical component in the autonomous attitude determination of aerospace vehicles. Compared to other attitude sensors, the star sensor offers higher attitude accuracy, low power consumption, small volume, and strong autonomy. It plays an important role in high-precision remote sensing, astronomical navigation, and other fields. Star extraction is an essential part of the star sensor in the process of working. Its accuracy and the number of extracted stars affect the performance of the star sensor. This paper proposes a method of star extraction based on the combination of the Improved Optical Flow Method (IOFM) and Dynamic Filtering (DF) named IOFM-DF. Based on the optical flow method, the motion characteristics of stars in the time and space domains are considered. Due to the difference between the star and noise in the motion trajectory, dynamic filtering is used to reduce the influence of noise from the star image on the extraction effect of the star. Considering the statistical properties of the motion trajectories of multiple stars, the cosine distance of the motion track between the extracted point and the star is calculated to predict the probability that the extracted point belongs to the star. IOFM-DF can extract and track stars in the star image for a low signal-to-noise ratio. Experimental results show that IOFM-DF increases the number of star extractions by at least 30% compared to traditional methods. This research is important to improve the accuracy and performance of star sensors.
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