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.

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.

Parameter Estimation and Cramer-Rao Bound in Wideband Bistatic MIMO Radar System

2015 ◽  
Vol 713-715 ◽  
pp. 651-655 ◽  
Author(s):  
Li Li
Keyword(s):  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Radar System ◽  
Novel Approach ◽  
Direction Of Departure ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Cramer Rao Bound

The problem of target localization and parameter estimation in wideband bistatic Multiple-Input Multiple-Output (MIMO) radar system is considered. In this paper, we use a novel approach to estimate Doppler stretch and time delay in fractional Fourier transform (FRFT) domain. We also develop two sub-array models to accurately estimate the direction-of-departure (DOD) and the direction-of-arrival (DOA). Furthermore, the Cramér-Rao bound for target parameter estimation is derived and computed in closed form. Parameter estimation performances are evaluated and studied theoretically and via simulations

scholarly journals A Barrage Jamming Strategy Based on CRB Maximization against Distributed MIMO Radar

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2453 ◽  
Author(s):  
Guangyong Zheng ◽  
Siqi Na ◽  
Tianyao Huang ◽  
Lulu Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Parameters Estimation ◽  
Swarm Optimization ◽  
Counter Measures ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Simulation Results ◽  
Cramer Rao Bound

Distributed multiple input multiple output (MIMO) radar has attracted much attention for its improved detection and estimation performance as well as enhanced electronic counter-counter measures (ECCM) ability. To protect the target from being detected and tracked by such radar, we consider a barrage jamming strategy towards a distributed MIMO. We first derive the Cramer–Rao bound (CRB) of target parameters estimation using a distributed MIMO under barrage jamming environments. We then set maximizing the CRB as the criterion for jamming resource allocation, aiming at degrading the accuracy of target parameters estimation. Due to the non-convexity of the CRB maximizing problem, particle swarm optimization is used to solve the problem. Simulation results demonstrate the advantages of the proposed strategy over traditional jamming methods.

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.

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 Spatial Differencing Reconstruction Based Low-Angle DOA Estimation with MIMO Radar

2018 ◽  
Vol 36 (1) ◽  
pp. 182-188
Author(s):  
Qin Zhang ◽  
Linrang Zhang ◽  
Junpeng Shi ◽  
Yannian Zhou ◽  
Yaning Liu
Keyword(s):  
Multiple Input Multiple Output ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Spatial Diversity ◽  
Mimo Radar ◽  
Estimation Accuracy ◽  
Signal Model ◽  
Estimation Performance ◽  
Multiple Input ◽  
Input Multiple Output

Due to the multipath effect, the direction of arrival (DOA) estimation performance for low-angle targets decreases greatly. To overcome this problem, this paper proposes a spatial differencing reconstruction based DOA estimation algorithm by using the received signal model of multiple input multiple output (MIMO) radar. Combining with the spatial diversity of MIMO radar, the proposed method can first use the multipath echo power to select the best signal. Then, a spatial differencing based iterative scheme is developed to reduce the effect of additive noise, resulting in a better estimation performance for low-angle targets. Simulation results show that the proposed method has better advantages in suppressing noise and improving estimation accuracy.

scholarly journals Low-Grazing Angle Detection in Compound-Gaussian Clutter with Hybrid MIMO Radar

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Jincan Ding ◽  
Haowen Chen ◽  
Hongqiang Wang ◽  
Xiang Li ◽  
Zhaowen Zhuang
Keyword(s):  
Multiple Input Multiple Output ◽  
Grazing Angle ◽  
Mimo Radar ◽  
Ratio Test ◽  
Linear Quadratic ◽  
Signal Model ◽  
Radar Systems ◽  
Multiple Input ◽  
Multipath Effects ◽  
Input Multiple Output

This paper focuses on the target detection in low-grazing angle using a hybrid multiple-input multiple-output (MIMO) radar systems in compound-Gaussian clutter, where the multipath effects are very abundant. The performance of detection can be improved via utilizing the multipath echoes. First, the reflection coefficient considering the curved earth effect is derived. Then, the general signal model for MIMO radar is introduced in low-grazing angle; also, the generalized likelihood test (GLRT) and generalized likelihood ratio test-linear quadratic (GLRT-LQ) are derived with known covariance matrix. Via the numerical examples, it is shown that the derived GLRT-LQ detector outperforms the GLRT detector in low-grazing angle, and both performances can be enhanced markedly when the multipath effects are considered.

scholarly journals Cognitive MIMO Frequency Diverse Array Radar with High LPI Performance

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Ling Huang ◽  
Kuandong Gao ◽  
Zhiming He ◽  
Jingye Cai
Keyword(s):  
Optimization Problem ◽  
Target Location ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Beam Pattern ◽  
Multiple Input ◽  
Convex Problem ◽  
Input Multiple Output ◽  
Frequency Diverse Array ◽  
Low Probability

Frequency diverse array (FDA) has its unique advantage in realizing low probability of intercept (LPI) technology for its dependent beam pattern. In this paper, we proposed a cognitive radar based on the frequency diverse array multiple-input multiple-output (MIMO). To implement LPI of FDA MIMO transmit signals, a scheme for array weighting design is proposed, which is to minimize the energy of the target location and maximize the energy of the receiver. This is based on the range dependent characteristics of the frequency diverse array transmit beam pattern. To realize the objective problem, the algorithm is proposed as follows: the second-order nonconvex optimization problem is converted into a convex problem and solved by the bisection method and convex optimization. To get the information of target, the FDA MIMO radar is proposed to estimate the target parameters. Simulation results show that the proposed approach is effective in decreasing the detection probability of radar with lossless detection performance of the receive signal.

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