FOD Detection Method Based on Iterative Adaptive Approach for Millimeter-Wave Radar.

Using millimeter-wave radar to scan and detect small foreign object debris (FOD) on an airport runway surface is a popular solution in civil aviation safety. Since it is impossible to completely eliminate the interference reflections arising from strongly scattering targets or non-homogeneous clutter after clutter cancellation processing, the consequent high false alarm probability has become a key problem to be solved. In this article, we propose a new FOD detection method for interference suppression and false alarm reduction based on an iterative adaptive approach (IAA) algorithm, which is a non-parametric, weighted least squares-based iterative adaptive processing approach that can provide super-resolution capability. Specifically, we first obtain coarse FOD target information by data preprocessing in a conventional detection method. Then, a refined data processing step is conducted based on the IAA algorithm in the azimuth direction. Finally, multiple pieces of information from the two steps above are used to comprehensively distinguish false alarms by fusion processing; thus, we can acquire accurate FOD target information. Real airport data measured by a 93 GHz radar are used to validate the proposed method. Experimental results of the test scene, which include golf balls with a diameter of 43 mm, were placed about 300 m away from radar, which show that the proposed method can effectively reduce the number of false alarms when compared with a traditional FOD detection method. Although metal balls with a diameter of 50 mm were placed about 660 m away from radar, they also can obtain up to 2.2 times azimuth super-resolution capability.

Sensor Fusion-Based Approach to Eliminating Moving Objects for SLAM in Dynamic Environments.

Accurate localization and reliable mapping is essential for autonomous navigation of robots. As one of the core technologies for autonomous navigation, Simultaneous Localization and Mapping (SLAM) has attracted widespread attention in recent decades. Based on vision or LiDAR sensors, great efforts have been devoted to achieving real-time SLAM that can support a robot's state estimation. However, most of the mature SLAM methods generally work under the assumption that the environment is static, while in dynamic environments they will yield degenerate performance or even fail. In this paper, first we quantitatively evaluate the performance of the state-of-the-art LiDAR-based SLAMs taking into account different pattens of moving objects in the environment. Through semi-physical simulation, we observed that the shape, size, and distribution of moving objects all can impact the performance of SLAM significantly, and obtained instructive investigation results by quantitative comparison between LOAM and LeGO-LOAM. Secondly, based on the above investigation, a novel approach named EMO to eliminating the moving objects for SLAM fusing LiDAR and mmW-radar is proposed, towards improving the accuracy and robustness of state estimation. The method fully uses the advantages of different characteristics of two sensors to realize the fusion of sensor information with two different resolutions. The moving objects can be efficiently detected based on Doppler effect by radar, accurately segmented and localized by LiDAR, then filtered out from the point clouds through data association and accurate synchronized in time and space. Finally, the point clouds representing the static environment are used as the input of SLAM. The proposed approach is evaluated through experiments using both semi-physical simulation and real-world datasets. The results demonstrate the effectiveness of the method at improving SLAM performance in accuracy (decrease by 30% at least in absolute position error) and robustness in dynamic environments.

Foreign Object Debris Automatic Target Detection for Millimeter-Wave Surveillance Radar.

Foreign Object Debris (FOD) refers to any foreign material on the airfield that may injure and threaten the aircraft and airport system. Due to the complex background on the airfield pavement and weak target echoes in long-distance monitoring, it is not easy to detect objects of various types and sizes. The existing FOD radar system's detection method has a short effective range, and the detectable objects' radar cross-section intensity is no less than -20 dBsm. In this paper, we propose an integrated FOD automatic target detection algorithm for millimeter-wave (MMW) surveillance radar to improve small target detection under long-range conditions of over 660 m. The signal form of FOD and a clutter model of ground clutter received by millimeter-wave radar are primarily utilized and established theoretically. The runway edge detection means that it is employed based on the in-continuity features as the runway region of interest during the automatic extraction step. Following the clutter map constant false alarm detection algorithm, we utilize a time-domain algorithm that functions as the vital detection processor. Moreover, an explicit definition of the FOD detection performance is developed in a characteristic quantitative way. This criterion involves an absolute reference value for all FOD radar systems. The well-designed FOD frequency-modulated continuous-wave MMW surveillance radar is utilized, and actual experiments are carried out in a real airport in Beijing, China. The results validate the proposed method's effectiveness and the superior performance of FOD target detection in long-range situations.

Time-Varying Kelvin Wake Model and Microwave Velocity Observation.

In the synthetic aperture radar (SAR) imaging of ship-induced wakes, it is difficult to obtain the Doppler velocity of a Kelvin wake due to the lack of time-varying wake models and suitable radar equipment. The conventional Kelvin wake investigation based on the static Kelvin wake model failed to reflect time-varying characteristics, which are significant in the application of the Kelvin wake model. Therefore, a time-varying Kelvin wake model with consideration of geometric time-varying characteristics and the hydrodynamic equation is proposed in this paper, which reflects the wake's time-varying change lacking in the conventional Kelvin wake investigation. The Doppler velocity measurement, measured by a specially designed radar, can be exploited to verify the time-varying model by the comparison of velocity fields. Ground-based multi-input multi-output (MIMO) millimeter wave radar imaging through the simultaneous switching of transceiver channels was used to obtain the Doppler velocity for the first time. Finally, promising results have been achieved, which are in good agreement with our proposed model in consideration of the experimental scene. The proposed time-varying model and radar equipment provide velocity measurements for the Kelvin wake observation, which contains huge application potential.

An Optical MEMS Acoustic Sensor Based on Grating Interferometer.

Acoustic detection is of great significance because of its wide applications. This paper reports a Micro-Electro-Mechanical System (MEMS) acoustic sensor based on grating interferometer. In the MEMS structure, a diaphragm and a micro-grating made up the interference cavity. A short-cavity structure was designed and fabricated to reduce the impact of temperature on the cavity length in order to improve its stability against environment temperature variations. Besides this, through holes were designed in the substrate of the grating to reduce the air damping of the short-cavity structure. A silicon diaphragm with a 16.919 µm deep cavity and 2.4 µm period grating were fabricated by an improved MEMS process. The fabricated sensor chip was packaged on a conditioning circuit with a laser diode and a photodetector for acoustic detection. The output voltage signal in response to an acoustic wave is of high quality. The sensitivity of the acoustic sensor is up to -15.14 dB re 1 V/Pa @ 1 kHz. The output signal of the high-stability acoustic sensor almost unchanged as the environment temperature ranged from 5 °C to 55 °C.

A Novel Orthogonal Waveform Separation Scheme for Airborne MIMO-SAR Systems.

In recent years, multi-input multi-output (MIMO) synthetic aperture radar (SAR) systems, which can promote the performance of 3D imaging, high-resolution wide-swath remote sensing, and multi-baseline interferometry, have received considerable attention. Several papers on MIMO-SAR have been published, but the research of such systems is seriously limited. This is mainly because the superposed echoes of the multiple transmitted orthogonal waveforms cannot be separated perfectly. The imperfect separation will introduce ambiguous energy and degrade SAR images dramatically. In this paper, a novel orthogonal waveform separation scheme based on echo-compression is proposed for airborne MIMO-SAR systems. Specifically, apart from the simultaneous transmissions, the transmitters are required to radiate several times alone in a synthetic aperture to sense their private inner-aperture channels. Since the channel responses at the neighboring azimuth positions are relevant, the energy of the solely radiated orthogonal waveforms in the superposed echoes will be concentrated. To this end, the echoes of the multiple transmitted orthogonal waveforms can be separated by cancelling the peaks. In addition, the cleaned echoes, along with original superposed one, can be used to reconstruct the unambiguous echoes. The proposed scheme is validated by simulations.

A Novel Scheme for MIMO-SAR Systems Using Rotational Orbital Angular Momentum.

The vortex electromagnetic (EM) wave with orbital angular momentum (OAM) brings a new degree of freedom for synthetic aperture radar (SAR) imaging, although to date, its application to multi-input multi-output (MIMO) SAR has not yet been widely reported. In this paper, an orbital angular momentum (OAM)-based MIMO-SAR system is proposed. The rotational Doppler Effect (RDE) of vortex EM waves offers a novel scheme for an OAM-based MIMO-SAR system. By transmitting the rotational vortex EM waves, echoes of different OAM modes can be discriminated by a bandpass filter in the range-Doppler domain. The performance of the proposed scheme is independent of the time-variant channel responses, and the wider beam width of the vortex EM waves delivers, for the same antenna aperture size, better performance in terms of swath width and azimuth resolution, in contrast to the plane EM waves. Moreover, the spatial diversity of vortex EM waves shows great potential to enhance the MIMO-SAR system applications, which involve high-resolution wide-swath remote sensing, 3-D imaging, and radar-communication integration. The proposed scheme is verified by proof-of-concept experiments. This work presents a new application of vortex EM waves, which facilitates the development of new-generation and forthcoming SAR systems.

Demonstration of a microwave photonic synthetic aperture radar based on photonic-assisted signal generation and stretch processing.

A microwave photonic synthetic aperture radar (MWP SAR) is developed and experimentally demonstrated. In the transmitter, microwave photonic frequency doubling is used to generate a linearly-frequency-modulated (LFM) radar signal; while in the receiver, photonic stretch processing is employed to receive the reflection signal. The presented MWP SAR operates in Ku band with a bandwidth of 600MHz, and is evaluated through a series of inverse SAR imaging tests both in a microwave anechoic chamber and in a field trial. Its imaging performance verifies that the proposed MWP SAR works perfect and shows the potential of overcoming the conventional radar bandwidth bottleneck.

The Drosha-Independent MicroRNA6778-5p/GSK3ß Axis Mediates the Proliferation of Gastric Cancer Cells.

Background: Gastric cancer (GC) is a primary cause of cancer death around the world. Previous studies have found that Drosha plays a significant role in the development of tumor cells. Soon after, we unexpectedly found that the expression of microRNA6778-5p (miR6778-5p) is unconventionally high in the gastric cancer cells low-expressing Drosha. So, we designed the Drosha interference sequence and recombined it into a lentiviral vector to construct Drosha knockdown lentivirus and transfected the Drosha knockdown lentivirus into gastric cancer cells to establish Drosha knockdown gastric cancer cell lines. We aimed to explore the effect of microRNA6778-5p on the proliferation of gastric cancer cells with Drosha knockdown and its intrinsic mechanism. Methods: We designed the Drosha interference sequence and recombined it into a lentiviral vector to construct Drosha knockdown lentivirus and transfected the Drosha knockdown lentivirus into gastric cancer cells to establish Drosha knockdown gastric cancer cell lines. After transfecting miR6778-5p mimics and inhibitor into gastric cancer cell lines with Drosha knockdown, the expression levels of miR6778-5p mimics in Drosha low-expressing gastric cancer cells increased, while miR6778-5p inhibitor decreased the expression levels of miR6778-5p. The Cell Counting Kit-8 (CCK-8) experiment was used to detect the proliferation ability of gastric cancer cells after overexpression or knockdown of miR6778-5p and bioinformatics predicted the relationship between miR6778-5p and glycogen synthase kinase-3ß (GSK3ß). Results: After infection with the Drosha knockdown lentivirus, Drosha's mRNA and protein levels were significantly downregulated in gastric cancer cells. The expression levels of miR6778-5p mimics in Drosha low-expressing gastric cancer cells increased, while miR6778-5p inhibitor decreased the expression levels of miR6778-5p. Overexpression of miR6778-5p significantly enhanced the proliferation ability of Drosha low-expression gastric cancer cells; on the contrary, knocking down miR6778-5p weakened the proliferation ability of Drosha low-expression gastric cancer cells. Bioinformatics predicted that miR6778-5p targeted glycogen synthase kinase-3ß (GSK3ß) and the mRNA and protein levels of GSK3ß decreased significantly after overexpression of miR6778-5p. Conclusion: miR6778-5p promotes the proliferation of Drosha low-expressing gastric cancer cells by targeting GSK3ß.