scholarly journals Tomographic Performance of Multi-Static Radar Formations: Theory and Simulations

2021 ◽  
Vol 13 (4) ◽  
pp. 737
Author(s):  
Ilgin Seker ◽  
Marco Lavalle
Keyword(s):  
Noise Suppression ◽  
Multiple Input Multiple Output ◽  
Radar Signal ◽  
Surface Layers ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Pros And Cons ◽  
The Cost ◽  
Observation Geometry ◽  
Azimuth Resolution

3D imaging of Earth’s surface layers (such as canopy, sub-surface, or ice) requires not just the penetration of radar signal into the medium, but also the ability to discriminate multiple scatterers within a slant-range and azimuth resolution cell. The latter requires having multiple radar channels distributed in across-track direction. Here, we describe the theory of multi-static radar tomography with emphasis on resolution, SNR, sidelobes, and nearest ambiguity location vs. platform distribution, observation geometry, and different multi-static modes. Signal-based 1D and 2D simulations are developed and results for various observation geometries, target distributions, acquisition modes, and radar parameters are shown and compared with the theory. Pros and cons of multi-static modes are compared and discussed. Results for various platform formations are shown, revealing that unequal spacing is useful to suppress ambiguities at the cost of increased multiplicative noise. In particular, we demonstrate that the multiple-input multiple-output (MIMO) mode, in combination with nonlinear spacing, outperforms the other modes in terms of ambiguity, sidelobe levels, and noise suppression. These findings are key to guiding the design of tomographic SAR formations for accurate surface topography and vegetation mapping.

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.

Joint Channel Estimation and Data Detection for STBC MIMO-OFDM Wireless Communication System

2015 ◽  
Vol 24 (04) ◽  
pp. 1550059 ◽  
Author(s):  
Gajanan R. Patil ◽  
Vishwanath K. Kokate
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Data Detection ◽  
Channel Estimate ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Ofdm ◽  
The Cost ◽  
Joint Channel

This paper presents a joint channel estimation and data detection technique for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Initial estimate of the channel is obtained using semi-blind channel estimation (SBCE). The whitening rotation (WR)-based orthogonal pilot maximum likelihood (OPML) method is used to obtain the channel estimate. The estimate is further enhanced by extracting information through the received data symbols. The performance of the proposed estimator is studied under various channel models. The simulation study shows that this approach gives better performance over training-based channel estimation (TBCE) and OPML SBCE methods but at the cost of higher computational complexity.

scholarly journals Controlling Initial and Final Radii to Achieve a Low-Complexity Sphere Decoding Technique in MIMO Channels

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Fatemeh Eshagh Hosseini ◽  
Shahriar Shirvani Moghaddam
Keyword(s):  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Sphere Decoding ◽  
Mimo Channels ◽  
Threshold Factor ◽  
Multiple Input ◽  
Input Multiple Output ◽  
The Cost ◽  
Practical Constraints

In order to apply sphere decoding algorithm in multiple-input multiple-output communication systems and to make it feasible for real-time applications, its computational complexity should be decreased. To achieve this goal, this paper provides some useful insights into the effect of initial and the final sphere radii and estimating them effortlessly. It also discusses practical ways of initiating the algorithm properly and terminating it before the normal end of the process as well as the cost of these methods. Besides, a novel algorithm is introduced which utilizes the presented techniques according to a threshold factor which is defined in terms of the number of transmit antennas and the noise variance. Simulation results show that the proposed algorithm offers a desirable performance and reasonable complexity satisfying practical constraints.

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.

Study on Multiple-Input Multiple-Output Synthetic Aperture Sonar Composite Acoustic Imaging Technique

2013 ◽  
Vol 333-335 ◽  
pp. 1175-1179
Author(s):  
Ting Ting Teng ◽  
Da Jun Sun ◽  
Yu Zhang ◽  
Cong Huang
Keyword(s):  
Imaging Technique ◽  
Multiple Input Multiple Output ◽  
Synthetic Aperture ◽  
Synthetic Aperture Sonar ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Imaging Sonar ◽  
Cross Track ◽  
Along Track ◽  
Azimuth Resolution

The azimuth resolution of imaging sonar lies on the aperture of the sensor array. In the paper, the Multiple-input Multiple-output Synthetic Aperture Sonar (MIMO-SAS) composite acoustic imaging technique was applied to imaging sonar equipped on the movable platform. The azimuth resolutions of both cross-track direction and along-track direction were obtained. The simulation results demonstrate that comparing with the conventional imaging technique Single-Input Multiple-output (SIMO), the azimuth resolution of cross-track direction is improved since the virtual array aperture of MIMO technique, and the azimuth resolution of along-track direction is obtained since the synthetic aperture of SAS technique. The simulation results are consistent with the theoretic value of the azimuth resolution.

scholarly journals A PE-MUSIC Algorithm for Sparse Array in MIMO Radar

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yucai Pang ◽  
Song Liu ◽  
Yun He
Keyword(s):  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Music Algorithm ◽  
Sparse Arrays ◽  
Sparse Array ◽  
Direction Of Departure ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Array Aperture ◽  
The Cost

Larger array aperture is provided by sparse arrays than uniform ones, which can improve the angle estimation resolution and reduce the cost of system evidently. However, manifold ambiguity is introduced due to the array sparsity. In this paper, a Power Estimation Multiple-Signal Classification (PE-MUSIC) algorithm is proposed to solve the manifold ambiguity of arbitrary sparse arrays for uncorrelated sources in Multiple-Input Multiple-Output (MIMO) radar. First, the paired direction of departure (DOD) and direction of arrival (DOA) are obtained for all targets by MUSIC algorithm, including the true and spurious ones; then, the well-known Davidon–Fletcher–Powell (DFP) algorithm is applied to estimate all targets’ power values, among which the value of a spurious target trends to zero. Therefore, the ambiguity of sparse array in MIMO radar can be cleared. Simulation results verify the effectiveness and feasibility of the method.

scholarly journals Channel Estimation Approach with Low Pilot Overhead in FBMC/OQAM Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jun Sun ◽  
Xiaomin Mu ◽  
Dejin Kong ◽  
Qian Wang ◽  
Xinmin Li ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Filter Bank ◽  
Multiple Input Multiple Output ◽  
Performance Loss ◽  
Filter Bank Multicarrier ◽  
Error Ratio ◽  
Multiple Input ◽  
Bit Error Ratio ◽  
Input Multiple Output ◽  
The Cost

In filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) systems, a large pilot overhead is required due to the existence of the imaginary interference. In this paper, we present an approach to reduce the pilot overhead of channel estimation. A part of pilot overhead is used for transmitting data, and compensating symbols are required and designed to remove the imaginary interference. It is worthwhile to point out that the power of compensating symbols can be helpful for data recovery; hence, the proposed approach decreases the overhead of pilots significantly without the cost of additional pilot energy. In addition, the proposed scheme is extended into multiple input multiple output systems without the performance loss. Compared with the conventional preamble consisting of 3 columns symbols, the pilot overhead is equivalent to 2 column symbols in the proposed preamble. To verify the proposed preamble, numerical simulations are carried out with respects to bit error ratio.

Design and Implementation of a Low-Complexity Multiuser Vector Precoder

2012 ◽  
Vol 3 (1) ◽  
pp. 31-48 ◽  
Author(s):  
Maitane Barrenechea ◽  
Luis Barbero ◽  
Mikel Mendicute ◽  
John S. Thompson
Keyword(s):  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Performance Loss ◽  
Dirty Paper Coding ◽  
Multiple Input ◽  
Input Multiple Output ◽  
The Cost ◽  
Complexity Constraints ◽  
Novel Design

Precoding techniques are used in the downlink of multiuser multiple-input multiple-output (MIMO) systems in order to separate the information data streams aimed at scattered user terminals. Vector precoding (VP) is one of the most promising non-linear precoding schemes, which achieves a performance close to the optimum albeit impractical dirty paper coding (DPC) with a feasible complexity. This contribution presents a novel design for the hardware implementation of a high-throughput vector precoder based on the Fixed Sphere Encoder (FSE) algorithm. The proposed fixed-complexity scheme greatly reduces the complexity of the most intricate part of VP, namely the search for the perturbing signal in an infinite lattice. Additionally, an optimized reduced-complexity implementation is presented which considerably reduces the resource usage at the cost of a small performance loss. Provided simulation results show the better performance of the proposed vector precoder in comparison to other fixed-complexity approaches, such as the K-Best precoder, under similar complexity constraints.

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.

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