▁ability ▁of ▁using ▁and ▁combining ▁data ▁from ▁different ▁sens ors ▁( ant enn as ) ▁in ▁order ▁to ▁deal ▁with ▁specific ▁estimation ▁task ▁( sp atial ▁and ▁temporal ▁processing ). ▁ ▁In ▁addition ▁to ▁the ▁information ▁that ▁can ▁be ▁extracted ▁from ▁the ▁collected ▁data ▁the ▁framework ▁uses ▁the ▁advantage ▁prior ▁knowledge ▁about ▁the ▁geometry ▁of ▁the ▁sensor ▁array ▁to ▁perform ▁the ▁estimation ▁task . ▁ ▁Array ▁processing ▁is ▁used ▁in ▁rad ar , ▁son ar , ▁se ism ic ▁expl oration , ▁anti - j am ming ▁and ▁wireless ▁ ▁communic ations . ▁One ▁of ▁the ▁main ▁advantages ▁of ▁using ▁array ▁processing ▁along ▁with ▁an ▁array ▁of ▁sens ors ▁is ▁a ▁smaller ▁foot - print . ▁ ▁The ▁problems ▁associated ▁with ▁array ▁processing ▁include ▁the ▁number ▁of ▁sources ▁used , ▁their ▁direction ▁of ▁arrival s , ▁and ▁their ▁signal ▁wave forms . ▁▁ ▁There ▁are ▁four ▁assumptions ▁in ▁array ▁processing . ▁ ▁The ▁first ▁assumption ▁is ▁that ▁there ▁is ▁uniform ▁propag ation ▁in ▁all ▁directions ▁of ▁is otrop ic ▁and ▁non - dis pers ive ▁medium . ▁ ▁The ▁second ▁assumption ▁is ▁that ▁for ▁far ▁field ▁array ▁processing , ▁the ▁radius ▁of ▁propag ation ▁is ▁much ▁greater ▁than ▁size ▁of ▁the ▁array ▁and ▁that ▁there ▁is ▁plane ▁wave ▁propag ation . ▁ ▁The ▁third ▁assumption ▁is ▁that ▁there ▁is ▁a ▁zero ▁mean ▁white ▁noise ▁and ▁signal , ▁which ▁shows ▁un cor relation . ▁ ▁Finally , ▁the ▁last ▁assumption ▁is ▁that ▁there ▁is ▁no ▁coupling ▁and ▁the ▁cal ibration ▁is ▁perfect . ▁