Detectors with Enhanced Range Estimation Capabilities

2021 ◽  
pp. 103-153
Author(s):  
Chengpeng Hao ◽  
Danilo Orlando ◽  
Jun Liu ◽  
Chaoran Yin
Keyword(s):  
Range Estimation

Flare range estimation: Evaluation of aids.

1970 ◽  
Author(s):  
Robert L. Hilgendorf ◽  
John C. Simons
Keyword(s):  
Range Estimation

Joint Angle, Velocity, and Range Estimation Using 2D MUSIC and Successive Interference Cancellation in FMCW MIMO Radar System

2020 ◽  
Vol E103.B (3) ◽  
pp. 283-290
Author(s):  
Jonghyeok LEE ◽  
Sunghyun HWANG ◽  
Sungjin YOU ◽  
Woo-Jin BYUN ◽  
Jaehyun PARK
Keyword(s):  
Interference Cancellation ◽  
Joint Angle ◽  
Mimo Radar ◽  
Radar System ◽  
Successive Interference Cancellation ◽  
Range Estimation

Physiological pitch range estimation from a brief speech input: A study on a bilingual parallel speech corpus

2020 ◽  
Author(s):  
Wei Zhang ◽  
Yanlu Xie ◽  
Jinsong Zhang
Keyword(s):  
Range Estimation ◽  
Speech Corpus ◽  
Pitch Range ◽  
Speech Input

scholarly journals Fast Target Localization Method for FMCW MIMO Radar via VDSR Neural Network

2021 ◽  
Vol 13 (10) ◽  
pp. 1956
Author(s):  
Jingyu Cong ◽  
Xianpeng Wang ◽  
Xiang Lan ◽  
Mengxing Huang ◽  
Liangtian Wan
Keyword(s):  
Neural Network ◽  
Continuous Wave ◽  
Super Resolution ◽  
Mimo Radar ◽  
Target Localization ◽  
Estimation Accuracy ◽  
Low Resolution ◽  
Range Estimation ◽  
Resolution Image ◽  
Resolution Imaging

The traditional frequency-modulated continuous wave (FMCW) multiple-input multiple-output (MIMO) radar two-dimensional (2D) super-resolution (SR) estimation algorithm for target localization has high computational complexity, which runs counter to the increasing demand for real-time radar imaging. In this paper, a fast joint direction-of-arrival (DOA) and range estimation framework for target localization is proposed; it utilizes a very deep super-resolution (VDSR) neural network (NN) framework to accelerate the imaging process while ensuring estimation accuracy. Firstly, we propose a fast low-resolution imaging algorithm based on the Nystrom method. The approximate signal subspace matrix is obtained from partial data, and low-resolution imaging is performed on a low-density grid. Then, the bicubic interpolation algorithm is used to expand the low-resolution image to the desired dimensions. Next, the deep SR network is used to obtain the high-resolution image, and the final joint DOA and range estimation is achieved based on the reconstructed image. Simulations and experiments were carried out to validate the computational efficiency and effectiveness of the proposed framework.

Remaining Driving Range Estimation Framework for Electric Vehicles in Platooning Applications

2021 ◽  
Author(s):  
Maxavier Lamantia ◽  
Zifei Su ◽  
Pingen Chen
Keyword(s):  
Electric Vehicles ◽  
Range Estimation ◽  
Driving Range

FDA-MIMO radar for DOD, DOA, and range estimation: SA-MCFO framework and RDMD algorithm

2021 ◽  
pp. 108209
Author(s):  
Cheng Wang ◽  
Xiaofei Zhang ◽  
Jianfeng Li
Keyword(s):  
Mimo Radar ◽  
Range Estimation

Pitch Range Estimation with Multi features and MTL-DNN Model

2018 ◽  
Author(s):  
Qi Zhang ◽  
Chong Cao ◽  
Tiantian Li ◽  
Yanlu Xie ◽  
Jinsong Zhang
Keyword(s):  
Range Estimation ◽  
Pitch Range
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