Sensor alignment and compensation for composite tracking

The integration of multiple sensors for the purpose of forming an integrated air picture has been intensely investigated in recent years. Assuming no sensor biases and minimal communication latencies, the optimal picture can be formed when all the sensor information is communicated to each network node. The state vectors for a given target at each node should be very similar. However, this does not occur in the presence of sensor bias which has an adverse effect on tracking performance. A method to account for the location, measurement, and attitude biases of the sensors must be employed to improve the accuracy of the target state estimates. This paper presents an absolute sensor alignment method to estimate the sensor bias in a multi-target environment. The output of the alignment process is used to compensate the sensor measurements employed in the tracking process. A comparison is made between the composite tracks generated using compensated and uncompensated measurements from multiple sensors.