An improved MUSIC algorithm for high resolution image reconstruction

The rapid progress in miniaturization and integration of micro-structured devices such as integrated circuits has recently increased the demand for a high resolution diagnosis tool. To meet this need, we have developed a highly resolvable fault locator named 3D Laser Microvision, which can nondestructively see through objects with high accuracy. This system is essentially a laser radar that works in a frequency domain rather than a time domain. Instead of sending a narrow pulse into an object, the wavelength of the laser is step-wisely changed ranging from 1.5 /spl mu/m to 1.6 /spl mu/m. At each step, the amplitude and phase of the reflected light from the object are measured and stored in a computer. The inner structure of the object, that is, where refractive indices vary abruptly, is reconstructed by processing these stored data. When a fast Fourier transform is used as the signal processing method, the spatial resolution is 12 /spl mu/m which is limited by the wavelength scanning range. We propose an improved adaptive spatial smoothing technique in the multiple signal classification (MUSIC) algorithm to overcome this limitation and verify its superior performance compared with the conventional MUSIC algorithm by numerical simulation.