Transmit Energy Focusing for DOA Estimation in MIMO Radar with Colocated Antennas (1007.0436v1)

Abstract: In this paper, we propose a transmit beamspace energy focusing technique for multiple-input multiple-output (MIMO) radar with application to direction finding for multiple targets. The general angular directions of the targets are assumed to be located within a certain spatial sector. We focus the energy of multiple (two or more) transmitted orthogonal waveforms within that spatial sector using transmit beamformers which are designed to improve the signal-to-noise ratio (SNR) gain at each receive antenna. The subspace decomposition-based techniques such as MUSIC can then be used for direction finding for multiple targets. Moreover, the transmit beamformers can be designed so that matched-filtering the received data to the waveforms yields multiple (two or more) data sets with rotational invariance property that allows applying search-free direction finding techniques such as ESPRIT for two data sets or parallel factor analysis (PARAFAC) for more than two data sets. Unlike previously reported MIMO radar ESPRIT/PARAFAC-based direction finding techniques, our method achieves the rotational invariance property in a different manner combined also with the transmit energy focusing. As a result, it achieves better estimation performance at lower computational cost. Particularly, the proposed technique leads to lower Cramer-Rao bound than the existing techniques due to the transmit energy focusing capability. Simulation results also show the superiority of the proposed technique over the existing techniques.

• The paper presents a transmit beamspace design that concentrates radar energy in target sectors to boost DOA estimation accuracy.
• It employs spheroidal sequences and convex optimization to maximize SNR and minimize energy leakage in colocated MIMO radar systems.
• Simulation results show improved source resolution probability, lower CRB, and reduced RMSE compared to traditional radar methods.

Transmit Energy Focusing for DOA Estimation in MIMO Radar with Colocated Antennas

The paper presents a novel approach for improving direction-of-arrival (DOA) estimation in multiple-input multiple-output (MIMO) radar systems, specifically focusing on systems with colocated antennas. The authors introduce a transmit beamspace energy focusing technique that optimizes the distribution of radar energy to enhance signal processing outcomes like DOA estimation. This research builds on existing methods by proposing a strategy that combines focused energy transmission with advanced subspace-based estimation techniques, such as MUSIC and ESPRIT, offering a robust solution with reduced computational demands.

Technical Overview

At the core of the approach is the concept of concentrating the transmitted radar energy within specific angular sectors where targets are expected. By doing so, the proposed method increases the signal-to-noise ratio (SNR) at the receive antennas, thereby improving the accuracy of DOA estimation. The paper outlines two distinct strategies for designing the transmit beamformers:

1. Spheroidal Sequences-Based Design: This method maximizes the energy concentration in the desired angular sector, ensuring a uniform distribution of energy across individual waveforms. By employing the discrete prolate spheroidal sequences, this approach achieves optimal beamspace dimension reduction and facilitates high-resolution DOA estimation.
2. Convex Optimization-Based Design: This technique minimizes the energy leakage into out-of-sector areas while preserving rotational invariance properties crucial for ESPRIT-based algorithms. It provides a mathematical framework for pinning the worst-case sidelobe levels below a user-defined threshold, ensuring focused energy transmission.

Performance and Results

The effectiveness of the proposed methods is evaluated against traditional and related MIMO radar techniques, such as transmit subaperturing (TS) and transmit array partitioning (TAP). Several key insights arise from the paper:

• Enhanced SNR and Aperture: The transmit beamspace focusing yields significant SNR gain per virtual array element, outperforming conventional MIMO radar schemes. The technique also achieves a larger effective array aperture, crucial for accurate DOA resolution.
• Lower Cramer-Rao Bound (CRB): By increasing the SNR and optimizing the virtual array aperture, the proposed methods achieve a lower CRB, indicating better estimation accuracy. Both stochastic and deterministic CRB analyses highlight the superior performance of the beamspace methodologies.
• Improved Probability of Source Resolution and RMSE: Simulation results demonstrate that the proposed beamspace techniques can resolve multiple sources with higher probability and lower root-mean-square error (RMSE) compared to existing methods, particularly in low to moderate SNR scenarios.

Implications and Future Directions

The implications of this research are substantial, promising significant advancements in radar-based surveillance, navigation, and communication systems. By optimizing the transmit energy focus, radar systems can achieve higher resolution and accuracy without necessitating hardware changes, aligning well with contemporary trends towards computational efficiency and energy management.

Future developments may explore the integration of this technique with more complex MIMO architectures, potentially involving adaptive algorithms that dynamically adjust their beamspace designs based on real-time environmental assessments or even machine learning models to predict and adapt to changing operational conditions.

In conclusion, this work offers a compelling enhancement to MIMO radar systems, potentially redefining strategies for energy distribution and target estimation accuracy in complex environments. The combination of mathematical rigor and practical enhancement sets a foundational precedence for ensuing research in radar signal processing and array design.