Statistically motivated design of input signals for modern ultrasonic array systems

Modern array systems allow for excitation of separate elements using arbitrary wave forms. This is utilized in pulse compression and coded excitation techniques to improve the imaging performance. Such techniques are however somewhat inflexible since they use predefined excitation schemes. This paper presents a more flexible method for optimizing the input signals to an ultrasonic array in such a way that the scattering strengths at arbitrarily chosen control points in the insonified object can be estimated with as small an error as possible, measured with a mean squared error criteria. The statistically motivated method is based on a linear model of the array imaging system and the method takes into account both prior information regarding the scattering strengths and measurement errors. The input signals are found by using genetic optimization and are constrained to have finite duration and bounds on the maximum amplitudes. Different constellations of control points, and different signal-to-noise ratios, yield different excitation schemes. The design approach finds multiple selective focal laws when choosing relatively well separated control points and when the control points are closely spaced, the resulting excitations result in more diffuse fields. Because of the flexibility in choosing the control points, the design method will be useful when developing transmission schemes aiming at fast imaging of large image areas using few transmissions.