ACCURACY IN ARMAMENTS


BIVARIATE APPROACH Bivariate Normal Impact Distribution, where ρ = Correlation(x, y).


APPLICATIONS OF VARIOUS METRICS There are times when some of these dis- persion metrics may be more desirable than others, depending on the intended application. The use of certain metrics relies on the assumption that σx


= σy . This


null hypothesis can be easily tested with a variation of the F-test that is commonly used in statistics. These measures have varying levels of statistical efficiency asso- ciated with them. Depending on available resources, some may be much easier to calculate than others.


For example, a rifleman or Soldier zero- ing, or confirming zero on a shooting range, typically shoots three- to five-round groups and is concerned mainly with the difference between the aimpoint and the


observed CoI. This same rifleman hon- ing his or her marksmanship skills may be more interested in the distance between the two farthest points on the target, or ES. Though ES is one of the least efficient methods to calculate dispersion, in this case it is desired because of its simplicity; it requires no use of mathematics, and in fact does not even require (x, y) coordi- nates of the rounds on target. All that is needed is a straightedge to measure the two points that are farthest apart.


An entirely different application is used in ammunition Lot Acceptance Testing (LAT) for accuracy, in which a relatively small quantity of ammunition (a random sample) is pulled from a larger population (ammunition lot). The sample typically is tested in one or several rigid-mounted


OPERATING CHARACTERISTIC CURVE OC curve of the LAT performance difference due to dispersion metric.


accuracy barrels, which are used as gauges to minimize the weapon system’s influ- ence on shot dispersion, so that the ammunition may be judged solely on its performance. Often, with small-caliber ammunition, MR is used to measure dispersion. The MR technique uses the distance formula shown above to deter- mine the distance of each round from the CoI, and then takes the average of all of the points’ radial distances.


Other common methods are CPE (for some artillery and shoulder-fired rock- ets), RSD (the most efficient method), and EHS/EVS (for 7.62mm M118LR sniper ammunition).


In LAT accuracy testing, the total sample quantity, breakout of rounds per target vs. number of targets in the test, and the method used to calculate the dispersion of the rounds on each target all contribute to the risks associated with accepting or rejecting lots of material.


In determining LAT quantities and acceptance criteria, operating characteris- tic (OC) curves are often used. They are useful to the statistician and quality engi- neer in that they model the probability of acceptance, or P[a], of lots of mate- riel, given some rate of nonconformity (or some other characteristic) within the lot. Acceptance criteria are set with the objective of rejecting lots that fail to meet these criteria (“bad” materiel), and accept- ing lots that meet the criteria (“good” materiel). There are, however, two other


70 Army AL&T Magazine


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76  |  Page 77  |  Page 78  |  Page 79  |  Page 80  |  Page 81  |  Page 82  |  Page 83  |  Page 84  |  Page 85  |  Page 86  |  Page 87  |  Page 88  |  Page 89  |  Page 90  |  Page 91  |  Page 92  |  Page 93  |  Page 94  |  Page 95  |  Page 96  |  Page 97  |  Page 98  |  Page 99  |  Page 100  |  Page 101  |  Page 102  |  Page 103  |  Page 104  |  Page 105  |  Page 106  |  Page 107  |  Page 108  |  Page 109  |  Page 110  |  Page 111  |  Page 112  |  Page 113  |  Page 114  |  Page 115  |  Page 116  |  Page 117  |  Page 118  |  Page 119  |  Page 120  |  Page 121  |  Page 122  |  Page 123  |  Page 124  |  Page 125  |  Page 126  |  Page 127  |  Page 128  |  Page 129  |  Page 130  |  Page 131  |  Page 132  |  Page 133  |  Page 134  |  Page 135  |  Page 136