Waveform Optimization for Target Scattering Coefficients Estimation Under Detection and Peak-to-Average Power Ratio Constraints in Cognitive Radar

Chen, Peng; Wu, Lenan; Qi, Chenhao

doi:10.1007/s00034-015-0048-y

Cited by 13 publications

(26 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nevertheless, unimodular waveform may lead to the degradation of waveform performance [15]. To tackle this problem, some researchers had used a more general low-PAR constraint to replace the unimodular constraint to further improve the waveform performance [6,7,[14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Efficient Low-PAR Waveform Design Method for Extended Target Estimation Based on Information Theory in Cognitive Radar

Hao

Gong

2019

Entropy

View full text Add to dashboard Cite

This paper addresses the waveform design problem of cognitive radar for extended target estimation in the presence of signal-dependent clutter, subject to a peak-to-average power ratio (PAR) constraint. Owing to this kind of constraint and the convolution operation of the waveform in the time domain, the formulated optimization problem for maximizing the mutual information (MI) between the target and the received signal is a complex non-convex problem. To this end, an efficient waveform design method based on minimization–maximization (MM) technique is proposed. First, by using the MM approach, the original non-convex problem is converted to a convex problem concerning the matrix variable. Then a trick is used for replacing the matrix variable with the vector variable by utilizing the properties of the Toeplitz matrix. Based on this, the optimization problem can be solved efficiently combined with the nearest neighbor method. Finally, an acceleration scheme is used to improve the convergence speed of the proposed method. The simulation results illustrate that the proposed method is superior to the existing methods in terms of estimation performance when designing the constrained waveform.

show abstract

Section: Introductionmentioning

confidence: 99%

Efficient Low-PAR Waveform Design Method for Extended Target Estimation Based on Information Theory in Cognitive Radar

Hao

Gong

2019

Entropy

View full text Add to dashboard Cite

show abstract

“…Consider a collocated MIMO radar with M element ULA as the transmitter and N element ULA as the receiver [3][4][5][6][7], as Figure 2 shows, the transmit element lined in the x-axis and the receive element lined in the y-axis. The transmitter transmits M orthogonal waveforms, each through one antenna which are separately extracted through matched filtering at the receiver.…”

Section: System Modelmentioning

confidence: 99%

Position Estimation of Automatic-Guided Vehicle Based on MIMO Antenna Array

Chen

He²,

Cao

et al. 2018

Electronics

View full text Add to dashboard Cite

The existing positioning methods for the automatic guided vehicle (AGV) in the port can not achieve high location precision, Therefore, a novel multiple input multiple output (MIMO) antenna radar positioning scheme is proposed in this paper. The positioning problem for AGV is considered, and the joint estimation problem for direction of departure (DoD) and direction of arrival (DoA) is addressed in the multiple-input multiple-output (MIMO) radar system. With the radar detect the transponder and estimate the DoA/DoD, the relative location between the transponder and the AGV can be obtained. The corresponding Cramér–Rao lower bounds (CRLBs) for the target parameters are also derived theoretically. Finally, we compare the positioning accuracy of the traditional global position system (GPS) with the proposed MIMO radar system. Simulation results show that the proposed method can achieve better performance than the traditional GPS.

show abstract

“…where is adopted to control the estimation accuracy and can be usually set as = σ 2 w , and x denotes the sparse vector, the non-zero entries are the target scattering coefficients, and the positions of the non-zero entries indicate the DoA and DoD [16][17][18]24,25].…”

Section: System Model For Radar Subsystemmentioning

confidence: 99%

DoA and DoD Estimation and Hybrid Beamforming for Radar-Aided mmWave MIMO Vehicular Communication Systems

Chen

Cao

He³

et al. 2018

Electronics

Self Cite

View full text Add to dashboard Cite

Abstract:In millimeter wave (mmWave) communications, the feature of relatively large signal absorption and directional transmission render new challenges for wireless communications and signal processing. To further improve the performance of mmWave communications, a novel radar-aided mmWave communication (RAMC) approach is proposed, which can be used in vehicular communications. There are two parts in the proposed RAMC system, including the radar subsystem and the mmWave communication subsystem. In the radar subsystem, the bistatic co-prime multi-input and multi-output (MIMO) arrays are considered. With the radar antenna arrays, both the directions of departure (DoD) and the directions of arrival (DoA) are estimated. Additionally, the compressed sensing (CS)-based method is proposed to obtain the target positions. Using the estimated angle and position information, the channel estimation and feedback link of the mmWave communication subsystem can be eliminated. Moreover, a hybrid beamforming algorithm is proposed in the mmWave communication subsystem, which can overcome the shortage of the analog-only beamforming. Simulation results show that the better estimation performance can be achieved by the bistatic co-prime MIMO arrays than that by the traditional uniform linear arrays (ULA), and with the radar aided, the mmWave communication subsystem can reduce the beam search time, and the cell discovery time is improved significantly.

show abstract

Waveform Optimization for Target Scattering Coefficients Estimation Under Detection and Peak-to-Average Power Ratio Constraints in Cognitive Radar

Cited by 13 publications

References 24 publications

Efficient Low-PAR Waveform Design Method for Extended Target Estimation Based on Information Theory in Cognitive Radar

Efficient Low-PAR Waveform Design Method for Extended Target Estimation Based on Information Theory in Cognitive Radar

Position Estimation of Automatic-Guided Vehicle Based on MIMO Antenna Array

DoA and DoD Estimation and Hybrid Beamforming for Radar-Aided mmWave MIMO Vehicular Communication Systems

Contact Info

Product

Resources

About