Closed-form solution to directly design face waveforms for beampatterns using planar array

Cost-optimization through the minimization of hardware and processing costs with minimal loss in performance is an interesting design paradigm in evolving and emerging Multiple-Input-Multiple-Output (MIMO) radar systems. This optimization is a challenging task due to the increasing Radio Frequency (RF) hardware complexity as well as the signal design algorithm complexity in applications requiring high angular resolution. Towards addressing these, the paper proposes a low-complexity signal design framework, which incorporates a generalized time multiplex scheme for reducing the RF hardware complexity with a subsequent discrete phase modulation. The scheme further aims at achieving simultaneous transmit beamforming and maximum virtual MIMO aperture to enable better target detection and discrimination performance. Furthermore, the paper proposes a low-complexity signal design scheme for beampattern matching in the aforementioned setting. The conducted performance evaluation indicates that the listed design objectives are met.

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“…With the 4(N T − 1) atoms defined, the n-th element of the generated radiation pattern in (34) takes the following form,…”

Section: Two Channel Qpsk Based Designmentioning

confidence: 99%

Generalized Multiplexed Waveform Design Framework for Cost-Optimized MIMO Radar

Hammes

Shankar

Ottersten

2021

IEEE Trans. Signal Process.

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“…A closed-form covariance matrix design method is described in [27] to achieve the desired beam-pattern based on discrete Fourier transform (DFT) coefficients and Toeplitz matrices. An extension of the DFT-based methods to a planar-antennaarray for constant-modulus waveforms design can be found in [28] and [29]. Although the DFT-based techniques for matching the transmit beam-pattern benefit from a lower computational complexity, the performance is not satisfactory for small number of antennas.…”

Section: Introduction and Prior Workmentioning

confidence: 99%

Joint Optimization of Waveform Covariance Matrix and Antenna Selection for MIMO Radar

Bose

Khobahi

Soltanalian

2019

2019 53rd Asilomar Conference on Signals, Systems, and Computers

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Controlling the radar beam-pattern by optimizing the transmit covariance matrix is a well-established approach for performance enhancement in multiple-input-multiple-output (MIMO) radars. In this paper, we investigate the joint optimization of the waveform covariance matrix and the antenna position vector for a MIMO radar system to approximate a given transmit beam-pattern, as well as to minimize the cross-correlation of the received waveforms reflected back from the targets. We formulate this design task as a non-convex optimization problem and then propose a cyclic optimization approach to efficiently approximate its solution. We further propose a local binary search algorithm in order to efficiently design the corresponding antenna positions. We show that the proposed method can be extended to the more general case of approximating the given beam-pattern using a minimal number of antennas as well as optimizing their positions. Our numerical investigations demonstrate a great performance both in terms of accuracy and computational complexity, making the proposed framework a good candidate for usage in real-time radar waveform processing applications such as MIMO radar transmit beamforming for aerial drones that are in motion.

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“…To reduce the computational complexity, a closed-form covariance matrix design method was proposed in [14] based on discrete Fourier transform (DFT). The authors in [15] and [16] also applied the DFT-based technique to a planar-antenna-array, and developed a finitealphabet constant-envelope waveforms design algorithm for the desired beampattern. However, the performance of the DFT-based method is slightly worse for a small number of antennas.…”

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confidence: 99%

On the Design of Constant Modulus Probing Waveforms With Good Correlation Properties for MIMO Radar via Consensus-ADMM Approach

Wang

2019

IEEE Trans. Signal Process.

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In this paper, we design constant modulus probing waveforms with good correlation properties for collocated multiinput multi-output (MIMO) radar systems. The main content is as follows: first, we formulate the design problem as a fourth order polynomial minimization problem with constant modulus constraints. Then, by exploiting introduced auxiliary variables and their inherent structures, the polynomial optimization model is equivalent to a non-convex consensus minimization problem. Second, a customized alternating direction method of multipliers (ADMM) algorithm is proposed to solve the non-convex problem approximately. In the algorithm, all the subproblems can be solved analytically. Moreover, all subproblems except one subproblem can be performed in parallel. Third, we prove that the customized ADMM algorithm is theoretically-guaranteed convergent if proper parameters are chosen. Fourth, two variant ADMM algorithms, based on stochastic block coordinate descent and accelerated gradient descent, are proposed to reduce computational complexity and speed up the convergence rate. Numerical examples show the effectiveness of the proposed consensus-ADMM algorithm and its variants.

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Closed-form solution to directly design face waveforms for beampatterns using planar array

Cited by 7 publications

References 19 publications

Generalized Multiplexed Waveform Design Framework for Cost-Optimized MIMO Radar

Generalized Multiplexed Waveform Design Framework for Cost-Optimized MIMO Radar

Joint Optimization of Waveform Covariance Matrix and Antenna Selection for MIMO Radar

On the Design of Constant Modulus Probing Waveforms With Good Correlation Properties for MIMO Radar via Consensus-ADMM Approach

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