# A Novel Generalized Nested Array MIMO Radar for DOA Estimation with Increased Degrees of Freedom and Low Mutual Coupling

**Authors:** Zhongtian Yang, Zhengyang Bi, Ye Chen, Honghao Hao

PMC · DOI: 10.3390/s24123952 · Sensors (Basel, Switzerland) · 2024-06-18

## TL;DR

This paper introduces a new MIMO radar design that improves direction of arrival estimation by reducing sensor mutual coupling and increasing degrees of freedom.

## Contribution

A novel generalized nested array MIMO radar is proposed with O(N4) DOFs and reduced mutual coupling effects.

## Key findings

- The proposed GNA-MIMO radar achieves higher DOA estimation accuracy under mutual coupling.
- Closed-form expressions for sensor positions and DOFs are derived and validated through simulations.

## Abstract

In array signal processing, the mutual coupling among physical sensors can inevitably affect the estimation of the direction of arrival (DOA). Despite the fact that multiple-input and multiple-output (MIMO) radar can provide greater degrees of freedom (DOFs), the influence of mutual coupling is largely overlooked in many current MIMO radar designs. To tackle this issue, we propose the utilization of a generalized nested array (GNA) in transmitter array and we introduce an expansion factor into the nested array in the receiver array. Thereby, a novel GNA-MIMO radar is put forward. The proposed MIMO radar offers O(N4) consecutive DOFs with N sensors and avoids the adverse effects of high mutual coupling caused by closely located sensors. Furthermore, we derive the closed-form expressions for the position of physical sensors and the attainable consecutive DOFs of the proposed MIMO radar. Through simulation experiments, we demonstrate the superior accuracy of the proposed MIMO configuration in DOA estimation and angle resolution under the condition of mutual coupling effect.

## Full-text entities

- **Diseases:** injury to people or property (MESH:C000719191)
- **Chemicals:** GNA (-)

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC11207968/full.md

## Figures

9 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11207968/full.md

## References

31 references — full list in the complete paper: https://tomesphere.com/paper/PMC11207968/full.md

---
Source: https://tomesphere.com/paper/PMC11207968