Nagesh, SaravananSaravananNageshEnder, JoachimJoachimEnderGonzalez Huici, Maria AntoniaMaria AntoniaGonzalez Huici2022-10-282022-10-282022https://publica.fraunhofer.de/handle/publica/4280632-s2.0-85133552213Compressed Sensing (CS) has been proven to be an effective technique to handle computational loads of multiple input multiple output (MIMO) radar systems; additionally, when considering Code Division Multiple Access (CDMA) MIMO radars high sidelobes, which are artefacts of the waveform, can be mitigated. However, the question as to how the correlation properties of these sequences or the choice of array geometry contribute towards performance of CS algorithms, individually or jointly, has not been analysed. In this paper, we present a study investigating waveform orthogonality and array geometry as parameters influencing the CS algorithms reconstruction performance. The numerical simulations have been carried out for a 2 dimensional range-angle (RA) scene with multiple targets, reconstructed by a CS-CDMA MIMO system, transmitting different code sequences in combination with different array geometries. The results validate how the right combination of the array configuration and transmission waveform leads to lower estimation errors and an increased probability of success.enBPDNCompressed SensingMatch filterProbability of successRandom ArrayRange-Angle estimationSparse Signal ProcessingULAconference paper