scholarly journals Joint Design of Space-Time Transmit and Receive Weights for Colocated MIMO Radar

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2722 ◽  
Author(s):  
Ze Yu ◽  
Shusen Wang ◽  
Wei Liu ◽  
Chunsheng Li
Keyword(s):  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Space Time ◽  
Moving Targets ◽  
Joint Design ◽  
Waveform Diversity ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Single Input ◽  
Space Time Adaptive Processing

Compared with single-input multiple-output (SIMO) radar, colocated multiple-input multiple-output (MIMO) radar can detect moving targets better by adopting waveform diversity. When the colocated MIMO radar transmits a set of orthogonal waveforms, the transmit weights are usually set equal to one, and the receive weights are adaptively adjusted to suppress clutter based on space-time adaptive processing technology. This paper proposes the joint design of space-time transmit and receive weights for colocated MIMO radar. The approach is based on the premise that all possible moving targets are detected by setting a lower threshold. In each direction where there may be moving targets, the space-time transmit and receive weights can be iteratively updated by using the proposed approach to improve the output signal-to-interference-plus-noise ratio (SINR), which is helpful to improve the precision of target detection. Simulation results demonstrate that the proposed method improves the output SINR by greater than 13 dB.

scholarly journals Local Degree of Freedom of Clutter for Reduced-Dimension Space-Time Adaptive Processing with MIMO Radar

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Yiduo Guo ◽  
Jian Gong ◽  
Yu Xiao
Keyword(s):  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Space Time ◽  
Degree Of Freedom ◽  
Adaptive Processing ◽  
Local Degree ◽  
Input Multiple Output ◽  
Reduced Dimension ◽  
Dimension Space ◽  
Space Time Adaptive Processing

Degree of freedom (DOF) of clutter in the reduced-dimension (RD) domain, which is called local DOF (LDOF), is of great importance for RD MIMO-STAP (space-time adaptive processing for multiple-input multiple-output radar) algorithms. In this paper, the LDOF equivalence of different RD MIMO-STAP algorithms are firstly proved, and then a generalized LDOF estimation rule under different conditions is developed to estimate the clutter LDOF for MIMO radar effectively. The accuracy of the proposed rule is verified, and how to design RD MIMO-STAP processors under the guidance of the proposed rule is presented through numerical simulations.

scholarly journals Mainlobe Jamming Suppression Using Improved Frequency Diverse Array with MIMO Radar

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Guang-ming Li ◽  
Qun Zhang ◽  
Qi-yong Liu ◽  
Jia Liang ◽  
Dan Wang ◽  
...  
Keyword(s):  
Multiple Input Multiple Output ◽  
Logistic Map ◽  
Mimo Radar ◽  
Line Of Sight ◽  
Waveform Diversity ◽  
Multiple Beams ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Frequency Diverse Array ◽  
Simulation Results

Frequency diverse array (FDA) has attracted much attention in recent years due to its range-angle-dependent beampattern. Multiple-input multiple-output (MIMO) radar can offer waveform diversity to increase the virtual aperture length for azimuth coherent focus processing in radar imaging. Combining the advantages of FDA and MIMO radar, FDA-MIMO radar can steer multiple beams to different targets in the same line of sight (LOS) of radar with different waveforms. In this paper, an improved FDA model with the logistic map is proposed to get the aperiodic and range-angle uncoupling beampattern. Based on the proposed FDA, combining the FDA-MIMO radar, the waveform and chirp rate jitter techniques are adopted to mainlobe jamming suppression. Simulation results show the effectiveness of the proposed method.

Joint Beamforming and Space-Time Coding for MIMO Channels

2009 ◽  
pp. 264-285
Author(s):  
Biljana Badic ◽  
Jinho Choi
Keyword(s):  
Smart Antenna ◽  
Multiple Input Multiple Output ◽  
Space Time ◽  
Diversity Gain ◽  
Mimo Channels ◽  
Space Time Coding ◽  
Joint Design ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Time Coding

This chapter introduces joint beamforming (or precoding) and space-time coding for multiple input multiple output (MIMO) channels. First, we explain key ideas of beamforming and space- time coding and then we discuss the joint design of beamformer and space-time codes and its benefits. Beamforming techniques play a key role in smart antenna systems as they can provide various features, including spatially selective transmissions to increase the capacity and coverage increase. STC techniques can offer both coding gain and diversity gain over MIMO channels. Thus, joint beamforming and STC is a more practical approach to exploit both spatial correlation and diversity gain of MIMO channels. We believe that joint design will be actively employed in future standards for wireless communications.

scholarly journals Joint Design of the Transmit Beampattern and Angular Waveform for Colocated MIMO Radar under a Constant Modulus Constraint

2021 ◽  
Vol 13 (17) ◽  
pp. 3392
Author(s):  
Hao Zheng ◽  
Bo Jiu ◽  
Kang Li ◽  
Hongwei Liu
Keyword(s):  
Numerical Simulations ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Processing Strategy ◽  
Constant Modulus ◽  
Joint Design ◽  
Power Spectral ◽  
Key Points ◽  
Multiple Input ◽  
Input Multiple Output

In this paper, we investigate the joint design of a transmit beampattern and angular waveform (AW) for colocated multiple-input multiple-output (MIMO) radars. The importance of the AW in the proposed signal processing strategy is first clarified, and then, two optimization models are established, which are aimed at either the power spectral density (PSD) design or the spectral compatibility and similarity design of the AW. There are two main differences between the proposed models and existing models. First, instead of matching a desired template or maximizing the transmit power on specific regions, the transmit beampattern in this paper is optimized to approach several key points, which guarantees the high transmit gain and the flexible adjustment of each beam gain. Second, instead of optimizing the performance of the transmit waveform, only the characteristics of the AW are examined, and they can be constrained quantitatively according to their relationship with the transmit gain. The two models can be unified into the same framework, and an efficient algorithm is proposed to solve the problem under a constant modulus constraint. The convergence of the proposed algorithm is demonstrated, and some improvements to reduce the computational complexity are proposed. Numerical simulations showed that compared to the existing methods, the proposed approach can be used to obtain a higher transmit gain, flexibly adjust each beam gain, and more accurately control the PSD, spectral compatibility, and similarity of the AW. Moreover, numerical simulations showed that, compared to the use of existing methods, the proposed algorithm has higher computational efficiency.

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