Space-Time Transmit Code and Receive Filter Design for Colocated MIMO Radar

Cui, Guolong; Yu, Xianxiang; Carotenuto, Vincenzo; Kong, Lingjiang

doi:10.1109/tsp.2016.2633242

Cited by 165 publications

(69 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The optimization problem in (24) is still nonconvex. In the following, we use the semidefinite relaxation (SDR) [36] to convert (24) (27) Clearly, (27) can be represented in the following generalized form as max…”

Section: A Max-min Designmentioning

confidence: 99%

“…Hence, the stochastic interpretation of the SDR in (31) allows us to obtain an approximate rank-one solution to (27). Specifically, given W ( +1) r , we can generate a set of independent and identically distributed Gaussian random vectors ξ i ∼ N (0, W ( +1) r ), i = 1, · · · , Q, where Q is the number of randomization trials.…”

Section: Algorithm 1 Generalized Dinkelbach's Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

Joint Waveform and Receiver Design for Co-Channel Hybrid Active-Passive Sensing With Timing Uncertainty

Wang

2020

IEEE Trans. Signal Process.

View full text Add to dashboard Cite

We consider a hybrid active-passive radar system that employs a wireless source as a passive illuminator of opportunity (IO) and a co-channel active radar transmitter operating in the same frequency band to seek spectral efficiency. The hybrid system can take advantage of the strengths of passive radar (e.g., energy efficiency, bi-/multi-static configuration, and spatial diversity) as well as those of active radar (dedicated transmitter, flexible transmit beam steering, waveform optimized for sensing, etc.). To mitigate the mutual interference and location-induced timing uncertainty between the radar and communication signals, we propose two designs for the joint optimization of the radar waveform and receive filters. The first is a max-min (MM) criterion that optimizes a worst-case performance metric over a timing uncertainty interval, and the other a weighted-sum (WS) criterion that forms a weighted sum of the performance metric at each delay within the delay uncertainty interval. Both design criteria result in nonconvex constrained optimization problems that are solved by sequential convex programming methods. When timing uncertainty vanishes, the two designs become identical and admit a simpler solution. Numerical results are presented to demonstrate the performance of the proposed hybrid schemes in comparison with conventional active-only and passive-only radar systems.

show abstract

Section: A Max-min Designmentioning

confidence: 99%

Section: Algorithm 1 Generalized Dinkelbach's Algorithmmentioning

confidence: 99%

Joint Waveform and Receiver Design for Co-Channel Hybrid Active-Passive Sensing With Timing Uncertainty

Wang

2020

IEEE Trans. Signal Process.

View full text Add to dashboard Cite

show abstract

“…We use the signal-to-interference-plusnoise-ratio (SINR) as the design metric. Note that a related waveform design problem based on SINR maximization for MIMO radar in the presence of clutter has been discussed in [19]- [25] (see also [26]- [30] and the references therein for similar waveform design problems for single-input-singleoutput (SISO) radar). In the cited references, algorithms have been developed for designing waveforms under certain practical constraints, including energy constraint, constant-modulus constraint, and a similarity constraint.…”

Section: Introductionmentioning

confidence: 99%

Polyphase Waveform Design for MIMO Radar Space Time Adaptive Processing

Tang

Tuck

Stoica

2020

IEEE Trans. Signal Process.

View full text Add to dashboard Cite

We consider the design of polyphase waveforms for ground moving target detection with airborne multiple-inputmultiple-output (MIMO) radar. Due to the constant-modulus and finite-alphabet constraint on the waveforms, the associated design problem is non-convex and in general NP-hard. To tackle this problem, we develop an efficient algorithm based on relaxation and cyclic optimization. Moreover, we exploit a reparameterization trick to avoid the significant computational burden and memory requirement brought about by relaxation. We prove that the objective values during the iterations are guaranteed to converge. Finally, we provide an effective randomization approach to obtain polyphase waveforms from the relaxed solution at convergence. Numerical examples show the effectiveness of the proposed algorithm for designing polyphase waveforms.Index Terms-Multiple-input-multiple-output (MIMO) radar, space time adaptive processing (STAP), signal-to-interferenceplus-noise-ratio (SINR), waveform design, polyphase waveforms.

show abstract

“…Recent works on JTRFD [10]- [16] can be divided into two categories. The first category concentrates on designing fast-time waveform transmission and receive filter with particular constraints on waveform characteristics, which essentially trade off the signal-to-noise ratio (SNR) for signal-to-clutterplus-noise ratio [10]- [12].…”

Section: Introductionmentioning

confidence: 99%

“…[13]- [16]. As a result, they have the potential of coping with Doppler related issues, such as uncertainty, and therefore, can offer enhanced resolution, superior detection, etc.…”

Section: Introductionmentioning

confidence: 99%

Joint Space-(Slow) Time Transmission with Unimodular Waveforms and Receive Adaptive Filter Design for Radar

Vorobyov

2018

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

View full text Add to dashboard Cite

A novel computationally efficient method for jointly designing the space-(slow) time (SST) transmission with unimodular waveforms and receive adaptive filter is developed for different radar configurations. The range sidelobe effect and Doppler characteristics are considered. In particular, we develop a novel approach for jointly synthesizing unimodular SST waveforms and minimum variance distortionless response receive adaptive filter for two cases of known Doppler information and presence of uncertainties on clutter bins. Corresponding non-convex optimization problems are formulated and efficient algorithms are derived. The main ideas of the algorithm developments are to decouple composite objective function of the formulated problems, generate minorizing surrogates, and then solve the joint design problem iteratively, but in closedform for each iteration by means of minorization-maximization technique. The proposed algorithms demonstrate good performance and have fast convergence speed and low complexity.

show abstract

Space-Time Transmit Code and Receive Filter Design for Colocated MIMO Radar

Cited by 165 publications

References 31 publications

Joint Waveform and Receiver Design for Co-Channel Hybrid Active-Passive Sensing With Timing Uncertainty

Joint Waveform and Receiver Design for Co-Channel Hybrid Active-Passive Sensing With Timing Uncertainty

Polyphase Waveform Design for MIMO Radar Space Time Adaptive Processing

Joint Space-(Slow) Time Transmission with Unimodular Waveforms and Receive Adaptive Filter Design for Radar

Contact Info

Product

Resources

About