Abstract
In this letter, a joint robust transmit/receive adaptive beamforming for multiple-input multiple-output (MIMO) radar based on probability-constrained optimization approach is developed in the case of Gaussian and arbitrary distributed mismatches present in both the transmit and receive signal steering vectors. A tight lower bound of the probability constraint is also derived by using duality theory. The formulated probability-constrained robust beamforming problem is nonconvex and NP-hard. However, we reformulate its cost function into a bi-quadratic function while the probability constraint splits into transmit and receive parts. Then, a block coordinate descent method based on second-order cone programming is developed to address the biconvex problem. Simulation results show an improved robustness of the proposed beamforming method as compared to the worst-case and other existing state-of-the-art joint transmit/receive robust adaptive beamforming methods for MIMO radar.
| Original language | English |
|---|---|
| Pages (from-to) | 112-116 |
| Number of pages | 5 |
| Journal | IEEE Signal Processing Letters |
| Volume | 23 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2016 |
| MoE publication type | A1 Journal article-refereed |
Keywords
- Duality
- Gaussian and arbitrary distributed mismatches
- MIMO radar
- probability-constrained optimization
- COLOCATED ANTENNAS
- COVARIANCE-MATRIX
- STEERING VECTOR
- DESIGN
- CONVERGENCE
- MINIMIZATION
- ALGORITHM
- ARRAYS
- ERRORS