α–β–γ tracking filters using acceleration measurements

BackgroundAlthough real-time tracking of moving objects using a variety of sensor parameters is in great demand in monitoring systems, no studies have reported α–$$\beta$$β–$$\gamma$$γ tracking filters using simultaneous measurements including acceleration. In this report, we propose and analyze two α–$$\beta$$β–$$\gamma$$γ filters using acceleration measurements, namely, position–acceleration-measured (PAM) and position–velocity–acceleration-measured (PVAM) α–$$\beta$$β–$$\gamma$$γ filters.FindingsBased on our previous work on position–velocity-measured (PVM) α–$$\beta$$β–$$\gamma$$γ filters, performance indices of the proposed filters are theoretically derived. Then, numerical analyses clarify the conditions under which the performance of the PAM filter surpasses that of the position-only-measured (POM) α–$$\beta$$β–$$\gamma$$γ filter. The results indicate that the PVAM filter achieves better accuracy than the other filters, even with a relatively large measurement noise.ConclusionsThis report verifies the effectiveness of the $$\alpha$$α–$$\beta$$β–$$\gamma$$γ filters using acceleration measurements based on numerical analyses using derived performance indices. These results are useful in the design of tracking systems including acceleration measurements (e.g., in deciding whether to use the measured acceleration to improve tracking filter performance).