This simulator models a delay and sum array using ten times the base ten logarithm of microphone count. Four microphones give about six point zero two decibels of gain, eight give nine point zero three, and sixteen give twelve point zero four. At twenty pixels per decibel the bars measure about one hundred twenty point four, one hundred eighty point six and two hundred forty point eight. Doubling count adds about three decibels in this formula. It is a modeled array gain, not proof that a deployed sensor detects a target or hears private speech. Received sound level subtracts twenty times the logarithm of range, with range floored at half a meter. A hypothetical source at eighty decibels and ten meters loses twenty decibels, giving sixty. At twenty meters it loses about twenty six point zero two, giving fifty three point nine eight. A modeled barrier adds eighteen decibels of loss, reducing the ten meter result to forty two. At five pixels per level unit the bars measure three hundred, two hundred sixty nine point nine and two hundred ten. Processed signal to noise then subtracts the entered noise floor and adds the modeled array gain. Real propagation and noise can differ from this simplified calculation. Optical coverage assumes a thirty six millimeter sensor width. Its horizontal field angle is twice the arctangent of sensor width divided by twice focal length. Coverage width at range simplifies to range times thirty six divided by focal length. At ten meters with a fifty millimeter lens, coverage is seven point two meters. At twenty meters it is fourteen point four. With nineteen twenty horizontal pixels, density halves from about two hundred sixty six point six seven to one hundred thirty three point three three pixels per meter. At one pixel per density unit, those bars are about two hundred sixty six point seven and one hundred thirty three point three. More coverage reduces spatial sampling density, but this does not model image recognition success.