Direction of Arrival Estimation for Coherent Signals’ Method Based on LSTM Neural Network

<table class="table-group" id="tab10"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left">Simulation cases</td><td class="align_center">LSTM</td><td class="align_center">MUSIC IMPROVE</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">Signal 1 and signal 2 are uncorrelated</td><td class="align_center">Yes</td><td class="align_center">Yes</td></tr><tr><td class="align_left">Signal 1 is correlated with signal 2</td><td class="align_center">Yes</td><td class="align_center">Yes</td></tr><tr><td class="align_left">Signal 1 and signal 2 are correlated but they are uncorrelated with signal 3</td><td class="align_center">Yes</td><td class="align_center">Yes</td></tr><tr><td class="align_left">All three signals are correlated</td><td class="align_center">Yes</td><td class="align_center">No</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Comparison of MUSIC-IMPROVE algorithm and LSTM model.</div>

Applied Computational Intelligence and Soft Computing

tab10

Table 10

Table 10: Direction of Arrival Estimation for Coherent Signals’ Method Based on LSTM Neural Network 