Sparse interferometer array systems can be the cost-effective precision radio-frequency emitter directionfinding
systems needed in military and civilian applications. High precision can be implemented by array
extent, while low cost is supported because the array is sparse. However, in the design process ambiguities
in the high dimensional array manifold space need to be evaluated, which typically can be mathematically
or empirically daunting. Here we describe a method to collapse the high dimensional design space, using
root-mean-squared phase differences for signals received at pairs of elements in the interferometer, to a twodimensional
histogram for ambiguity visualization and evaluation (HAVE). The histogram facilitates design
by presenting and locating interferometer ambiguities.
Design of interferometer arrays for radio frequency direction of arrival estimation involves optimizing conflicting requirements. For example, high resolution conflicts with low cost. Lower level requirements also invoke lower level design issues such as ambiguity in direction of arrival angle. A more efficient array design process is described here, which uses a genetic algorithm with a growing genome and fuzzy logic scoring. Extensive simulation software is also needed. Simulation starts with randomized small array configurations. These are then evaluated against the fitness functions with results scored using fuzzy logic. The best-fit of the population are combined to produce the next generation. A mutation function introduces slight randomness in some genomes. Finally, if the overall population scores well the size of the genome is increased until final genome size is consistent with the desired array resolution requirement. The genetic algorithm design process described here produced a number of array designs. The results indicate discrete stages or steps in the optimization and an interesting trade-off of lower resolution for greater accuracy.