scholarly journals Low Elevation Angle Estimation with Range Super-Resolution in Wideband Radar

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3104 ◽  
Author(s):  
Sha Huan ◽  
Man Zhang ◽  
Gane Dai ◽  
Huaguo Gan
Keyword(s):  
Grazing Angle ◽  
Elevation Angle ◽  
Super Resolution ◽  
Robust Estimator ◽  
Frequency Diversity ◽  
Angle Estimation ◽  
Structure Relationship ◽  
Radar Waveforms ◽  
Radar Applications ◽  
Wideband Radar

Height detection of a low elevation angle target is crucial in radar applications. Due to the presence of the multiple path reflections, elevation angle estimation is difficult with conventional narrowband radar waveforms. The reflection ground area parameters are especially hard to obtain for modeling. In this paper, we proposed a wideband, low elevation angle estimator based on range super-resolution, achieving a high robustness to variations in reflection coefficients. A relaxation (RELAX) algorithm was applied as the range super-resolution algorithm to separate the direct target echo and the reflected signal thanks to the relatively abundant frequency diversity. The grazing angle was obtained by synthesizing the steering vector of the direct signal and the range structure relationship between the two signal components. Theoretical analysis and simulation results confirmed the improved behavior of the proposed robust estimator in contrast to other conventional algorithms.

scholarly journals Tracking a Low-Angle Isolated Target via an Elevation-Angle Estimation Algorithm Based on Extended Kalman Filter with an Array Antenna

2021 ◽  
Vol 13 (19) ◽  
pp. 3938
Author(s):  
Hossein Darvishi ◽  
Mohammad Ali Sebt ◽  
Domenico Ciuonzo ◽  
Pierluigi Salvo Salvo Rossi
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Elevation Angle ◽  
Estimation Algorithm ◽  
Physical Parameters ◽  
Frequency Diversity ◽  
Angle Estimation ◽  
Low Snr ◽  
First Case ◽  
Multipath Signals

In a low-angle tracking situation, estimating the elevation angle is challenging due to the entrance of the multipath signals in the antenna’s main lobe. In this article, we propose two methods based on the extended Kalman filter (EKF) and frequency diversity (FD) process to estimate the elevation angle of a low-angle isolated target. In the first case, a simple weighting of the per-frequency estimates is obtained (termed WFD). Differently, in the second case, a matrix-based elaboration of the per-frequency estimates is proposed (termed MFD). The proposed methods are completely independent of prior knowledge of geometrical information and the physical parameters. The simulation results show that both methods have excellent performance and guarantee accurate elevation angle estimation in different multipath environments and even in very-low SNR conditions. Hence, they are both suitable for low-peak-power radars.

scholarly journals JOINT AZIMUTH AND ELEVATION ANGLE ESTIMATION USING MATRIX COMPLETION METHOD

2017 ◽  
Vol 57 ◽  
pp. 197-203
Author(s):  
Peixiang Tan ◽  
Yuntao Wu ◽  
Ge Yan ◽  
Jieyi Deng
Keyword(s):  
Matrix Completion ◽  
Elevation Angle ◽  
Angle Estimation

Improved Azimuth/Elevation Angle Estimation Algorithm for Three-Parallel Uniform Linear Arrays

2015 ◽  
Vol 14 ◽  
pp. 329-332 ◽  
Author(s):  
Hua Chen ◽  
Chunping Hou ◽  
Qing Wang ◽  
Ling Huang ◽  
Weiqing Yan ◽  
...  
Keyword(s):  
Elevation Angle ◽  
Estimation Algorithm ◽  
Angle Estimation ◽  
Linear Arrays

scholarly journals SELECTING THE LORENZ PARAMETERS FOR WIDEBAND RADAR WAVEFORM GENERATION

2011 ◽  
Vol 21 (09) ◽  
pp. 2539-2545 ◽  
Author(s):  
MATT S. WILLSEY ◽  
KEVIN M. CUOMO ◽  
ALAN V. OPPENHEIM
Keyword(s):  
Autocorrelation Function ◽  
Lorenz System ◽  
Power Level ◽  
Side Lobe ◽  
Spectral Leakage ◽  
System Parameters ◽  
Constant Envelope ◽  
Radar Waveforms ◽  
The Lorenz System ◽  
Wideband Radar

Radar waveforms based on chaotic systems have occasionally been suggested for a variety of radar applications. In this paper, radar waveforms are constructed with solutions from a particular chaotic system, the Lorenz system, and are called Lorenz waveforms. Waveform properties, which include the peak autocorrelation function side-lobe and the transmit power level, are related to the system parameters of the Lorenz system. Additionally, scaling the system parameters is shown to correspond to an approximate time and amplitude scaling of Lorenz waveforms and also corresponds to scaling the waveform bandwidth. The Lorenz waveforms can be generated with arbitrary time lengths and bandwidths and each waveform can be represented with only a few system parameters. Furthermore, these waveforms can then be systematically improved to yield constant-envelope output waveforms with low autocorrelation function sidelobes and limited spectral leakage.

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