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

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3853
Author(s):  
Fei Qin ◽  
Xiangxi Bu ◽  
Yunlong Liu ◽  
Xingdong Liang ◽  
Jihao Xin

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.

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2999 ◽  
Author(s):  
Yong Wang ◽  
Wen Wang ◽  
Mu Zhou ◽  
Aihu Ren ◽  
Zengshan Tian

In recent years, non-contact radar detection technology has been able to achieve long-term and long-range detection for the breathing and heartbeat signals. Compared with contact-based detection methods, it brings a more comfortable and a faster experience to the human body, and it has gradually received attention in the field of radar sensing. Therefore, this paper extends the application of millimeter-wave radar to the field of health care. The millimeter-wave radar first transmits the frequency-modulated continuous wave (FMCW) and collects the echo signals of the human body. Then, the phase information of the intermediate frequency (IF) signals including the breathing and heartbeat signals are extracted, and the Direct Current (DC) offset of the phase information is corrected using the circle center dynamic tracking algorithm. The extended differential and cross-multiply (DACM) is further applied for phase unwrapping. We propose two algorithms, namely the compressive sensing based on orthogonal matching pursuit (CS-OMP) algorithm and rigrsure adaptive soft threshold noise reduction based on discrete wavelet transform (RA-DWT) algorithm, to separate and reconstruct the breathing and heartbeat signals. Then, a frequency-domain fast Fourier transform and a time-domain autocorrelation estimation algorithm are proposed to calculate the respiratory and heartbeat rates. The proposed algorithms are compared with the contact-based detection ones. The results demonstrate that the proposed algorithms effectively suppress the noise and harmonic interference, and the accuracies of the proposed algorithms for both respiratory rate and heartbeat rate reach about 93%.


2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Antonio Fulvio Scannapieco ◽  
Alfredo Renga ◽  
Antonio Moccia

A dedicated system simulator is presented in this paper for indoor operations onboard small Unmanned Aerial Systems (UAS) by a novel millimeter wave radar sensor. The sensor relies on the principle of Synthetic Aperture Radar (SAR) applied to a Frequency Modulated Continuous Wave (FMCW) radar system. Input to the simulator are both design parameters for Synthetic Aperture Radar (SAR), which should be able to cope with the stringent requirements set by indoor operations, and information about platform navigation and observed scene. The scene generation task is described in detail. This is based on models for point target response on either a completely absorbing background or fluctuating background and ray tracing (RT) techniques. Results obtained from scene processing are finally discussed, giving further insights on expected results from high-resolution observation of an assigned control volume by this novel SAR sensor.


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