MIMO-OTH Radar: Signal Model for Arbitrary Placement and Signals With Non-Point Targets

2015 ◽  
Vol 63 (7) ◽  
pp. 1846-1857 ◽  
Author(s):  
Qian He ◽  
Xiaodong Li ◽  
Zishu He ◽  
Rick S. Blum
Keyword(s):  
Radar Signal ◽  
Signal Model

scholarly journals Evaluation of a class of NLFM radar signals

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Sebastian Alphonse ◽  
Geoffrey A. Williamson
Keyword(s):  
Search Space ◽  
Frequency Function ◽  
Radar Signal ◽  
Optimized Design ◽  
Nonlinear Frequency ◽  
Signal Design ◽  
Signal Model ◽  
Radar Systems ◽  
Comprehensive Comparison

AbstractSignal design is an important component for good performance of radar systems. Here, the problem of determining a good radar signal with the objective of minimizing autocorrelation sidelobes is addressed, and the first comprehensive comparison of a range of signals proposed in the literature is conducted. The search is restricted to a set of nonlinear, frequency-modulated signals whose frequency function is monotonically nondecreasing and antisymmetric about the temporal midpoint. This set includes many signals designed for smaller sidelobes including our proposed odd polynomial frequency signal (OPFS) model and antisymmetric time exponentiated frequency modulated (ATEFM) signal model. The signal design is optimized based on autocorrelation sidelobe levels with constraints on the autocorrelation mainlobe width and leakage of energy outside the allowed bandwidth, and we compare our optimized design with the best signal found from parameterized signal model classes in the literature. The quality of the overall best such signal is assessed through comparison to performance of a large number of randomly generated signals from within the search space. From this analysis, it is found that the OPFS model proposed in this paper outperforms all other contenders for most combinations of the objective functions and is expected to be better than nearly all signals within the entire search set.

Oil-Spills Detection in MIMO-SAR Radar Images by High Order Statistics

2013 ◽  
Vol 443 ◽  
pp. 649-652
Author(s):  
Yan Ling Luo
Keyword(s):  
Oil Spills ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Radar Signal ◽  
Future Research ◽  
Signal Model ◽  
Radar Images ◽  
Multiple Input ◽  
Input Multiple Output ◽  
High Order Statistics

MIMO radar (Multiple input multiple output radar) is a hot topic which gets lots of attention from researchers all around the world recently. It can achieve better detection performance than conventional phased radar. In this paper, the MIMO radar signal model is studied, and then the concept of MIMO radar is applied into SAR. The technique is employed to detect the oil spill in sea. At last, some conclusion is drawn. And some item for future research in presented also.

Multi-Target Direction Measurement of Bistatic MIMO Radar

2014 ◽  
Vol 556-562 ◽  
pp. 2797-2801
Author(s):  
Jing Fang Wang
Keyword(s):  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Radar Signal ◽  
Great Success ◽  
Two Dimensional ◽  
Signal Model ◽  
Bistatic Mimo Radar ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Technology

Multiple-input multiple output (MIMO) radar has been widespread concern in the domestic and foreign researchers. Bistatic radar draws on the great success of MIMO technology in the communications field, and it has many advantages over conventional radar. The direction angles estimations of bistatic MIMO radar are researched. To contrast traditional radar DOA estimates, the direction vector of the bistatic MIMO radar is the Knonecker plot of the emission vector and reception vector, that two-dimensional direction angles is estimated. To solve this problem, the principle of bistatic MIMO radar signal model is in-depthly researched.By proposing Capon dimensionality reduction method, the two-dimensional directions of the dual-based MIMO radar are estimated, and computer simulation is to verify the effectiveness of the method.

scholarly journals Multiband Radar Signal Coherent Processing Algorithm for Motion Target

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Tingjing Wang ◽  
Ying Zhang ◽  
Hua Zhao ◽  
Yanxin Zhang
Keyword(s):  
Radar Signal ◽  
Quadratic Term ◽  
Minimum Entropy ◽  
Signal Model ◽  
Quadratic Phase ◽  
Entropy Principle ◽  
Geometrical Theory Of Diffraction ◽  
And Performance ◽  
Difference Term ◽  
Phase Term

In real application, most aerial targets are movable. In this paper, an effective multiple subbands coherent processing method is proposed for moving target. Firstly, an echoed signal model of motion target based on geometrical theory of diffraction is established and the influence of velocity on range profile of the target is analyzed. Secondly, a method based on minimum entropy principle is used to compensate velocity. Then, incoherent factors including a quadratic phase term, a linear phase factor, a fixed factor, and an amplitude difference term are analyzed. Subsequently, efficient methods are applied to estimate other incoherent factors, except that the quadratic term is small enough to be ignored. Finally, the feasibility and performance of the proposed method are investigated through numerical simulation.

scholarly journals Ship Profile Imaging Using Multipath Backscattering

2019 ◽  
Vol 11 (7) ◽  
pp. 748
Author(s):  
Jean-Marc Le Caillec ◽  
Jérôme Habonneau ◽  
Ali Khenchaf
Keyword(s):  
Time Delays ◽  
Grazing Angle ◽  
Radar Signal ◽  
Point Scatterer ◽  
Signal Model ◽  
Range Resolution ◽  
Ship Recognition ◽  
Synthetic Aperture Radars ◽  
High Range Resolution Radar ◽  
High Range

This paper addresses the estimation of the height of a point scatterer over a sea surface via multipath exploitation for a High Range Resolution radar that is using pulse range compression, such as Synthetic Aperture Radars. We first focus our attention on the physical model, in particular on the specular/diffuse reflection coefficients, this coefficients being derived from the empirical Miller Brown and Vegh model. The gravity waves are also simulated since they modify the acquisition geometry such as the local grazing angle. Secondly, the signal model is derived, thus allowing an easy derivation of the time delays (direct echo and replicas), these time delays being converted into a height estimation for possible automatic ship recognition applications. Our algorithm is a non-conventional radar signal processing, in other words it uses the backscattered pulse over before range compression and demodulation. The aim of the paper is to understand for which radar and sea parameters, as well as acquisition scenes, it is possible to extract the scatterer height information using the multipath of the backscattered electromagnetic wave.

A Simulation System for MIMO Radar

2010 ◽  
Vol 121-122 ◽  
pp. 633-639
Author(s):  
Jian Kui Zeng ◽  
Zi Ming Dong
Keyword(s):  
Signal Processing ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Simulation System ◽  
Radar Signal ◽  
Signal Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Conventional Counterpart ◽  
Radar Technique

MIMO radar (Multiple input multiple output radar) is a novel radar technique developed recently. It can achieve better detection performance than conventional phased radar. In this paper, the MIMO radar signal model is studied, and then the signal processing flow of the MIMO radar is researched. At last, a simulation platform with the Matlab is established to testify the advantage of MIMO radar over its conventional counterpart.

scholarly journals Compressed Sensing for THz FMCW Radar 3D Imaging

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Shanshan Gu ◽  
Guangrong Xi ◽  
Lingyu Ge ◽  
Zhong Yang ◽  
Yizhi Wang ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
3D Imaging ◽  
Continuous Wave ◽  
Imaging System ◽  
Measurement Data ◽  
Radar Signal ◽  
Data Reconstruction ◽  
Signal Model ◽  
Fmcw Radar ◽  
Range Migration

A terahertz (THz) frequency-modulated continuous wave (FMCW) imaging radar system is developed for high-resolution 3D imaging recently. Aiming at the problems of long data acquisition periods and large sample sizes for the developed imaging system, an algorithm based on compressed sensing is proposed for THz FMCW radar 3D imaging in this paper. Firstly, the FMCW radar signal model is built, and the conventional range migration algorithm is introduced for THz FMCW radar imaging. Then, compressed sensing is extended for THz FMCW radar 3D imaging, and the Newton smooth L0-norm (NSL0) algorithm is presented for sparse measurement data reconstruction. Both simulation and measurement experiments demonstrate the feasibility of reconstructing THz images from measurements even at the sparsity rate of 20%.

scholarly journals Modified Radar Signal Model using NLFM

2019 ◽  
Vol 8 (2S3) ◽  
pp. 513-516
Keyword(s):  
Interference Mitigation ◽  
Matched Filter ◽  
Signal To Noise Ratio ◽  
Nonlinear Function ◽  
Side Lobe ◽  
Radar Signal ◽  
Target Range ◽  
Nonlinear Frequency ◽  
Good Resolution ◽  
Signal Model

Intended to the setback of high side lobes of the linear frequency modulation (LFM) signal, we put forward a new signal model using nonlinear frequency (NLFM) signal to overcome the issue. NLFM is a promising way for achieving lower signal to noise ratio, good resolution and better interference mitigation. The novel signal model is designed to enhance the target range estimation and to reduce the side lobe levels. In this paper, a new signal model is designed based on the principle of fusion of two stages. First stage is exponential based nonlinear function and the second stage is a linear function. The simulations were performed for the designed signal model and are compared with the NLFM signal designed using two stage LFM functions. Simulation results show that the designed signal has significant reduction in side lobe levels of the matched filter response

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