The　Kalman　filter　algorithms　are　computationally　intensive,　therefore,　parallel　processing　could　be　an　option　to　meet　the　timing　performance　requirements.　In　this　paper　detailed　research　and　experimentation　have　been　done　for　parallel　processing　of　the　Kalman　filter　and　the　Extended　Kalman　filter　based　on　operating　system　and　multiple　general　purpose　processors　that　support　shared　memory.　The　time　comparison　of　the　various　methods　is　analyzed　with　respect　to　real-time　spacecraft　vehicle　parameters　estimation　and　a　slight　time　reduction　in　the　parallel　Kaman　filter　has　been　observed　compared　with　sequential　method.