Antenna Array Design for Coherent MIMO Radar Networks

Janoudi, Vinzenz; Schoeder, Pirmin; Grebner, Timo; Schwarz, Dominik; Waldschmidt, Christian; Dickmann, Juergen; Appenrodt, Nils

doi:10.1109/radarconf2351548.2023.10149789

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…The quadratic fast time phase of ±2πμδ t t 2 , which leads to a loss of resolution [3], is removed by multiplying ( 21) and ( 22) with the complex conjugate phasor in the fast time dimension. These steps are combined into a single multiplication applied to the bistatic beat signal for all successive chirps…”

Section: A Frequency Offsetmentioning

confidence: 99%

“…Distributed cooperative radar networks are seen as an emerging technology in several technical areas. In the automotive world, where most vehicles are equipped with multiple radar sensors, a trend is towards combining single sensors nodes into a multistatic system and applying coherent processing [1], [2], [3], [4]. Ideas go even further, shifting from fixed-mounted radar nodes on a common frame, such as an automobile or unmanned aerial vehicle (UAV), to individually moving, uncoupled radar nodes.…”

Section: Introductionmentioning

confidence: 99%

“…In this case, all synchronization tasks need to be performed wirelessly, which poses considerable, challenges especially if phase coherency or even phase noise coherency is intended [19]. The works presented in [20], [21], and [3] introduce coherent processing schemes for bistatic frequencymodulated continuous-wave (FMCW) chirp sequence (CS) signals in an uncoupled radar network. Phase coherency is achieved there, but less attention is paid to phase noise effects.…”

Section: Introductionmentioning

confidence: 99%

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Constellation Estimation, Coherent Signal Processing, and Multiperspective Imaging in an Uncoupled Bistatic Cooperative Radar Network

Fenske,

Koegel,

Ghasemi

et al. 2024

IEEE J. Microw.

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Cooperative radar networks are a promising technology in various areas, such as vehicleto-infrastructure networks for automotive radar and radar remote sensing with UAVs. The use of widely distributed radar networks enables the detection of targets with complex scattering characteristics, as their coherent bistatic images are superior for forward scattering, and each monostatic image illuminates a scene from a different perspective. This work introduces a signal processing scheme that addresses two main challenges in this area: the coherent signal processing of uncoupled radar nodes and the self-localization of the nodes for radar image combination. A comprehensive signal model that incorporates time, frequency and phase incoherency is introduced. Based on this, an algorithm for constellation estimation, synchronization up to the carrier phase level, and multiperspective imaging is developed. The proposed approach is experimentally verified using commercially available 77 GHz single-input/multiple-output radar nodes. The measurements for different radar constellations and various target scenes show a self-localization accuracy below 6 cm in range and below 2.5 • for the incident angles. The resulting images of various scenes clearly indicate an information gain compared to single monostatic images due to the combination of bistatic and multiperspective monostatic images.

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Section: A Frequency Offsetmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Constellation Estimation, Coherent Signal Processing, and Multiperspective Imaging in an Uncoupled Bistatic Cooperative Radar Network

Fenske,

Koegel,

Ghasemi

et al. 2024

IEEE J. Microw.

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Signal Model for Coherent Processing of Uncoupled and Low Frequency Coupled MIMO Radar Networks

Janoudi,

Schoeder,

Grebner

et al. 2024

IEEE J. Microw.

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MIMO radar networks consisting of multiple independent radar sensors offer the possibility to create large virtual apertures and therefore provide high angular resolution for automotive radar systems. In order to increase the angular resolution, the network must be able to process all data phase coherently. Establishing phase coherency, without distributing the transmitted RF signal to all sensors, poses a significant challenge in the automotive frequency range of 76 GHz to 81 GHz. This paper presents a signal model for uncoupled and low frequency coupled radar networks. The requirements for phase coherent processing for uncoupled radar sensors are systematically derived from the signal model. The proposed signal processing methods, which establish coherency, are sub-aperture based. Both the signal model and the proposed signal processing methods are verified by measurements with radar sensor networks composed of 2 and 3 radar sensors, providing 768 and 1728 virtual channels respectively. Measurements verify that phase noise is insignificant in the process of establishing coherency in uncoupled and low frequency coupled radar networks.INDEX TERMS Automotive radar networks, signal processing, multiple-input-multiple-output.

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