Algebraic solution for three‐dimensional TDOA/AOA localisation in multiple‐input–multiple‐output passive radar

2018 ◽  
Vol 12 (1) ◽  
pp. 21-29 ◽  
Author(s):  
Ali Noroozi ◽  
Mohammad Ali Sebt
2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Chia-Hao Wu ◽  
Jwo-Shiun Sun ◽  
Bo-Shiun Lu

This paper presents a compact four-element multiple-input–multiple-output (MIMO) antenna design operating within the WiFi 802.11 ac bands (5.2–5.84 GHz) for a smartwatch. The antenna is fabricated using a polyamide substrate and embedded into the strap of a smartwatch model; the strap is created using three-dimensional etching of plastic materials. The four-element MIMO antenna is formed by four monopole antennas, has a simple structure, and is connected to the system ground plane of the smartwatch. Due to the stub and notched block between two antennas and the slit in the system ground, the four-element MIMO antenna exhibits favorable isolation. Moreover, the envelope correlation coefficient of the antennas is considerably lower than 0.005 in the operating band. The measured −6 dB impedance bandwidths of the four elements of the antenna (Ant1–Ant4) with the human wrist encompass the WiFi 802.11 ac range of 5.2–5.84 GHz; moreover, an isolation of more than 20 dB is achieved. The measured antenna efficiency with and without a phantom hand are 45%–55% and 93%–97%, respectively.


Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4839
Author(s):  
Kong ◽  
Xu

A fully-polarimetric unitary multiple signal classification (UMUSIC) tomography algorithm is proposed, which can be used for acquiring high-resolution three-dimensional (3D) imagery, in a polarimetric multiple-input multiple-output synthetic aperture radar (MIMO-SAR) with a small number of baselines. In terms of the elevation resolution, UMUSIC provides an improvement over standard MUSIC by utilizing the conjugate of the complex sample data and converting the complex covariance matrix into a real matrix. The combination of UMUSIC and fully-polarimetric data permits a further reduction of the noise of the sample covariance matrix, which is obtained through pixel averaging of multiple two-dimensional (2D) images. Considering the consistency of four polarizations, this algorithm not only makes scattering centers have the same estimated height in four polarizations, but it also improves the estimation accuracy. Simulation results show that this algorithm outperforms the popular distributed compressed sensing (DCS). Image processing of measured data of an aircraft model using a multiple-input multiple-output synthetic aperture radar (MIMO-SAR) with six baselines is presented to validate the proposed algorithm.


Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3374 ◽  
Author(s):  
Fang Zhou ◽  
Jiaqiu Ai ◽  
Zhangyu Dong ◽  
Jiajia Zhang ◽  
Mengdao Xing

In multiple-input multiple-output synthetic aperture radar (MIMO–SAR) signal processing, a reliable separation of multiple transmitted waveforms is one of the most important and challenging issues, for the unseparated signal will degrade the performance of most MIMO–SAR applications. As a solution to this problem, a novel APC–MIMO–SAR system is proposed based on the azimuth phase coding (APC) technique to transmit multiple waveforms simultaneously. Although the echo aliasing occurs in the time domain and Doppler domain, the echoes can be separated well without performance degradation by implementing the azimuth digital beamforming (DBF) technique, comparing to the performance of the orthogonal waveforms. The proposed MIMO–SAR solution based on the APC waveforms indicates the feasibility and the spatial diversity of the MIMO–SAR system. It forms a longer baseline in elevation, which gives the potential to expand the application of MIMO–SAR in elevation, such as improving the performance of multibaseline InSAR and three-dimensional SAR imaging. Simulated results on both a point target and distributed targets validate the effectiveness of the echo separation and reconstruction method with the azimuth DBF. The feasibility and advantage of the proposed MIMO–SAR solution based on the APC waveforms are demonstrated by comparing with the imaging result of the up- and down-chirp waveforms.


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