scholarly journals Signal Model and Parameter Estimation for Colocated Mimo Radar

2022 ◽  
Vol 16 ◽  
pp. 7-11
Author(s):  
Moein , Ahmadi ◽  
Kamal Mohamed-Pour
Keyword(s):  
Parameter Estimation ◽  
Closed Form ◽  
Covariance Matrix ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Training Data ◽  
Low Rank ◽  
Unknown Parameters ◽  
Signal Model ◽  
Ml Estimation

In this paper, we consider the signal model and parameter estimation for multiple-input multiple-output (MIMO) radar with colocated antennas on stationary platforms. Considering internal clutter motion, a closed form of the covariance matrix of the clutter signal is derived. Based on the proposed closed form and low rank property of the clutter covariance matrix and by using the singular value decomposition, we have proposed a subspace model for the clutter signal. Following the proposed signal model, we have provided maximum likelihood (ML) estimation for its unknown parameters. Finally, the application of the proposed ML estimation in space time adaptive processing (STAP) is investigated in simulation results. Our ML estimation needs no secondary training data and it can be used in scenarios with nonhomogeneous clutter in range.

MIMO Radar Target Detection Performance Analysis with Unknown Parameters

2011 ◽  
Vol 403-408 ◽  
pp. 182-186
Author(s):  
Wei Wei Liu ◽  
Ning Cao ◽  
Hao Lu ◽  
Ju Rong Hu
Keyword(s):  
Performance Analysis ◽  
Multiple Input Multiple Output ◽  
Likelihood Estimation ◽  
Mimo Radar ◽  
Low Rank ◽  
Radar Target ◽  
Signal Power ◽  
Unknown Parameters ◽  
Multiple Input ◽  
Input Multiple Output

Motivated by the development of Multiple-Input Multiple-Output (MIMO) communication, MIMO radar has drawn considerable attention. While, to design of MIMO radar detector, transmitting signal power and noise are usually assumed known in advance, but in practice we may need to estimate the transmitting signal power and noise first. In this paper, we introduce MIMO radar target performance analysis with unknown parameters. First transmitting signal energy is estimated by Maximum likelihood Estimation(MLE) when multipath satisfy special diversity condition and multipath has low rank. Then the detector in the Neyman-Pearson is developed and analyzed with estimated parameters. The simulation results show that the performance with unknown parameters is approximate to the detector with known parameters. The method proposed in this paper can be used to design the MIMO radar detectors with unknown parameters.

Cramer-Rao Bound for Parameter Estimation in Bistatic MIMO Radar

2014 ◽  
Vol 513-517 ◽  
pp. 3385-3388
Author(s):  
Li Li
Keyword(s):  
Parameter Estimation ◽  
Target Location ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Signal Model ◽  
Wideband Signal ◽  
Wideband Signals ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Cramer Rao Bound

The problem of Cramér-Rao bound for parameter estimation in wideband bistatic Multiple-Input Multiple-Output (MIMO) radar system is considered. In many applications, it is not appropriate to approximate the wideband signal by the narrowband model. In this paper, we propose a new wideband signal model to accurately estimate parameter for wideband signals from a moving target. The Cramér-Rao bound for target parameter estimation is derived and computed in closed form which shows that the optimal performance is achieved. Target location and parameter estimation performances are evaluated and studied theoretically and via simulations.

Cramer-Rao Bound for Parameter Estimation in Narrowband Bistatic MIMO Radar

2014 ◽  
Vol 556-562 ◽  
pp. 5034-5037 ◽  
Author(s):  
Li Li
Keyword(s):  
Parameter Estimation ◽  
Target Location ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Signal Model ◽  
Narrowband Signal ◽  
Multiple Input ◽  
Estimate Parameter ◽  
Input Multiple Output ◽  
Cramer Rao Bound

The problem of Cramer-Rao bound for parameter estimation in norrowband bistatic Multiple-Input Multiple-Output (MIMO) radar system is considered. In this paper, we propose a new narrowband signal model to accurately estimate parameter from a moving target. The Cramer-Rao bound for target parameter estimation is derived and computed in closed form which shows that the optimal performance is achieved. Target location and parameter estimation performances are evaluated and studied theoretically and via simulations.

scholarly journals MIMO Radar Accurate 3-D Imaging and Motion Parameter Estimation for Target with Complex Motions

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3961
Author(s):  
Ziying Hu ◽  
Wei Wang ◽  
Fuwang Dong ◽  
Ping Huang
Keyword(s):  
Parameter Estimation ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Motion Parameter ◽  
Least Square ◽  
Parametric Models ◽  
Imaging Method ◽  
Signal Model ◽  
Motion Parameter Estimation ◽  
Accurate Localization

In this paper, three-dimensional (3-D) multiple-input multiple-output (MIMO) radar accurate localization and imaging method with motion parameter estimation is proposed for targets with complex motions. To characterize the target accurately, a multi-dimensional signal model is established including the parameters on target 3-D position, translation velocity, and rotating angular velocity. For simplicity, the signal model is transformed into three-joint two-dimensional (2-D) parametric models by analyzing the motion characteristics. Then a gridless method based on atomic norm optimization is proposed to improve precision and simultaneously avoid basis mismatch in traditional compressive sensing (CS) techniques. Once the covariance matrix is obtained by solving the corresponding semi-definite program (SDP), estimating signal parameters via rotational invariance techniques (ESPRIT) can be used to estimate the positions, then motion parameters can be obtained by Least Square (LS) method, accordingly. Afterwards, pairing correction is carried out to remove registration errors by setting judgment conditions according to resolution performance analysis, to improve the accuracy. In this way, high-precision imaging can be realized without a spectral search process, and any slight changes of target posture can be detected accurately. Simulation results show that proposed method can realize accurate localization and imaging with motion parameter estimated efficiently.

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 The Spatially Separated Polarization Sensitive FDA-MIMO Radar: A New Antenna Structure for Unambiguous Parameter Estimation

2018 ◽  
Vol 173 ◽  
pp. 02015
Author(s):  
Binbin Li ◽  
Weixiong Bai ◽  
Qin Zhang ◽  
Guimei Zheng ◽  
Mingliang Zhang ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Music Algorithm ◽  
Range Estimation ◽  
Antenna Structure ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Random Frequency ◽  
Frequency Diverse Array

Joint DOA-range-polarization estimation with a novel radar system, i.e., spatially separated polarization sensitive random frequency diverse array based on multiple-input multiple-output (SS-PSRFDA-MIMO) radar, is discussed. The proposed array can obtain not only unambiguous range estimation but also polarization parameter estimation. Firstly, the signal model of SS-PSRFDA-MIMO radar is constructed. Secondly, dimension reduction multiple signal classification (DR-MUSIC) algorithm is extended to parameter estimation with the proposed array. Last, simulations demonstrate the proposed algorithm is effective to estimate parameter, and the performance of proposed array is better than that of polarization sensitive frequency diverse array based on MIMO radar. It is worth mentioning that the Cramér–Rao lower bound (CRLB) of range estimation with the proposed array is much lower than that of PSFDA-MIMO radar.

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