Joint Range-Angle Estimation Based on enhanced subspace-based Method in Nonlinear Frequency FDA-MIMO Radar

The challenge of accurately locating multi-target in complex environments has become increasingly critical as radar technology evolves. Traditional phased array radars utilize onedimensional measurement methods for range and angle estimation separately, resulting in the inability to efficiently distinguish between similar targets, which affects the ability to identify and track targets. Conventional approaches to mitigate range ambiguity, such as frequency staggering and pulse discarding, complicate the system and may degrade signal integrity. In contrast, frequency diverse array-multiple input multiple output (FDA-MIMO) radar utilizes fixed frequency offsets to create two-dimensional beams, thereby increasing the degrees of freedom for target detection. However, FDA-MIMO radar still encounters limitations in resolving range ambiguity. This article proposes a model for resolving range ambiguity through random logarithmic frequency offset, supported by both theoretical and experimental analyzes. Applicable to FDAMIMO radars with random logarithmic frequency offset, we propose two enhanced subspace-based two-dimensional algorithms for joint range-angle estimation, which demonstrate improved performance under low signal-to-noise ratio (low-SNR) conditions. The results indicate that our designed algorithms significantly enhance estimation accuracy and resolution, facilitating more effective multitarget detection in challenging environments.