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- Li, Jian, et al.
(author)
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Signal synthesis and receiver design for MIMO radar imaging
- 2008
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In: IEEE Transactions on Signal Processing. - 1053-587X .- 1941-0476. ; 56:8:2, s. 3959-3968
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Journal article (peer-reviewed)abstract
- Multiple-input-multiple-output (MIMO) radar is an emerging technology that has significant potential for advancing the state-of-the-art of modern radar. When orthogonal waveforms are transmitted, with M + N (N transmit and M receive) antennas, an MN-element filled virtual array can be obtained. To successfully utilize such an array for high-resolution MIMO radar imaging, constant-modulus transmit signal synthesis and optimal receive filter design play critical roles. We present in this paper a computationally attractive cyclic optimization algorithm for the synthesis of constant-modulus transmit signals with good auto- and cross-correlation properties. Then we go on to discuss the use of an instrumental variables approach to design receive filters that can be used to minimize the impact of scatterers in nearby range bins on the received signals from the range bin of interest (the so-called range compression problem). Finally, we present a number of numerical examples to demonstrate the effectiveness of the proposed approaches.
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| 2. |
- Xu, L, et al.
(author)
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ASEO : a method for the simultaneous estimation of single-trial event-related potentials and ongoing brain activities
- 2009
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In: IEEE Transactions on Biomedical Engineering. - 0018-9294 .- 1558-2531. ; 56:1, s. 111-121
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Journal article (peer-reviewed)abstract
- Cognitive functions are often studied by recording electric potentials from the brain over repeated presentations of a sensory stimulus or repeated performance of a motor action. Each repetition is called a trial. Recent work has demonstrated that contrary to the traditional view, the event-related potential (ERP) can vary from trial to trial and the background ongoing activity often contains rich information about the cognitive state of the brain. Based on such a variable signal plus ongoing activity model, an iterative parameter estimation method is proposed in which both the single-trial parameters of the ERP and the autoregressive representation of the ongoing activity are obtained simultaneously. This technique, referred to as the analysis of single-trial ERP and ongoing activities method, is first tested on simulation examples, and then applied to the local field potential recordings from monkeys performing a visuomotor task.
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