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This paper presents a framework for incorporating knowledge sources directly in the space-time beamformer of airborne adaptive radars. The algorithm derivation follows the usual linearly-constrained minimum-variance (LCMV) space-time beamformer with additional constraints based on a model of the clutter covariance matrix that is computed using available knowledge about the operating environment. This technique has the desirable property of reducing sample support requirements by "blending" the information contained in the observed radar data and the a priori knowledge sources. Applications of the technique to both full degree of freedom (DoF) and reduced DoF beamformer algorithms are considered. The performance of the knowledge-aided beam forming techniques are demonstrated using high-fidelity simulated X-band radar data  相似文献   
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Technology's prime mover in our culture is that special combination of management and engineering talents called the entrepreneur. The name is usually applied to the individual who has already made his move into organizationally independent status. The latent entrepreneur is here defined to be the same type, but one still buried in his parent organization. This paper discusses ways in which industry can foster and use the special self-motivating characteristics of such individuals during their latent stage. Entrepreneurship is a combination of full personal commitment to exploiting a perceived opportunity, the vision of a service to provide to society, and the placing of higher value on the free exercise of talents than on security. When employed in management of an existing company, the "captive entrepreneur" is the one who moves out against the organizational boundaries, and stretches his limits of authority. If his career satisfactions are not sufficient to him, he will bolt. The challenge to industry is to use this entrepreneurial drive. There appear to be sufficient advantages to industry to make the effort one of "enlightened self-interest".  相似文献   
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