An Up-Sampled Particle Filter Fusion Technique and Its Application in Synthetic Aperture Radar Imaging

Sun, Brian; Kenney, Russell H.; Yeary, Mark; Sigmarsson, Hjalti H.; McDaniel, Jay W.

doi:10.1109/jmw.2021.3123531

Cited by 6 publications

(6 citation statements)

References 33 publications

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“…Moreover, even potentially low-latency models, in addition to many post-processing techniques, rely upon auxiliary hardware such as IMUs to estimate parasitic platform motion parameters, an undesired system hardware overhead and additional source of error for edge devices if used in isolation [39], [44], [45], [46], [47]. A number of these promising algorithms also assume motion models such as pure singlemode platform vibration [25], [30], [46], [48] or long-scale translatory motion [49], neglecting the additional modes and high-frequency components present in most realistic applications.…”

Section: A Related Workmentioning

confidence: 99%

Anchor-Based, Real-Time Motion Compensation for High-Resolution mmWave Radar

Poole,

Arbabian

2024

IEEE J. Microw.

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In the modern domain of edge sensing and physically compact smart devices, mmWave radar has emerged as a prominent modality, simultaneously offering high-resolution perception capacity and accommodatingly small form factor. The inevitable presence of device motion, however, corrupts the received radar data, reducing target sensing capability and requiring active correction to address the resultant spectral "blurring". Existing motion compensation techniques utilize computationally intensive post-processing algorithms and/or auxiliary hardware, aspects ill-suited for resource-limited edge devices requiring minimal system latency and complexity. Early works also often consider motion dynamics such as pure single-mode vibration, neglecting additional modes as well as non-harmonic motion content. We resolve both of these limitations by presenting a real-time-compatible, generalized complex motion compensation algorithm capable of correcting multicomponent platform trajectories involving both non-harmonic transients and multimode harmonic vibration. The proposed anchor-based approach achieves average SNR gains of 24.9 dB and 19.7 dB across transient duration and target velocity, respectively, and average multimode harmonic suppressions of 38.9 dB and 29.4 dB across vibration parameters and target velocity, respectively. These results, combined with minimal latency (≤ 240 ms), low algorithmic complexity, and the elimination of any additional auxiliary sensors, render the proposed method suitable for deployment in typical edge sensing applications.INDEX TERMS Real-time sensing, mmWave radar, high-resolution radar, imaging radar, complex motion, deconvolution, radar signal processing, anchor point.

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Section: A Related Workmentioning

confidence: 99%

Anchor-Based, Real-Time Motion Compensation for High-Resolution mmWave Radar

Poole,

Arbabian

2024

IEEE J. Microw.

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“…For example, particle filters have been used to fuse data from multiple sensors to track target location over a sensor network that covers an area of interest [23], [24], [25], [26], [27], [28]. Furthermore, particle filters can be used in conjunction with inertial sensors for motion tracking applications [10]. This application was shown in [25], where fused data from visual sensors and an inertial sensor were used to track the motion of a robotic arm.…”

Section: Related Workmentioning

confidence: 99%

“…The particle filter mathematics are foundational to the proposed algorithm; specifically, the resampling techniques used are derived heavily from the particle filter. Specific details of the particle filter mathematics and the benefits of using the particle filter to interpolate position solutions are discussed in [10]. The method proposed in this article is applied to address the high positional accuracy required in SAR applications, as discussed in the next section, with a specific focus of miniaturizing the navigation system.…”

Section: Related Workmentioning

confidence: 99%

“…Such a technique would allow for pulsed SAR systems to no longer be constrained by the sampling rates of the IMU and GNSS systems. As demonstrated in [10], such a interpolation technique exists and is expanded upon in this work to be applied to multiple IMU systems.…”

Section: Sar Imagingmentioning

confidence: 99%

“…The motivation for the higher positional accuracy is to obtain highly focused images in synthetic aperture radar (SAR) systems. In SAR, the effects of positional errors are evident in the final image due to misalignment of phase from illuminated scatterers, as explained in [10]. Traditionally, large GNSS/IMU systems are utilized to obtain a higher positional accuracy.…”

Section: Introductionmentioning

confidence: 99%

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Reduced Navigation Error Using a Multi-Sensor Fusion Technique and Its Application in Synthetic Aperture Radar

Sun,

Kenney,

Yeary

et al. 2024

IEEE J. Microw.

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Modern navigation solutions rely on a combination of inertial measurement units (IMUs) and a global navigation satellite system (GNSS) receiver to estimate a navigating body's position. In order to produce a high-fidelity solution, the current approach is to utilize a single ultra-low bias navigational grade IMU in the system. However, these high-quality IMUs are expensive, bulky, heavy, and require significant power consumption. This article proposes the fusion of multiple lower-quality IMUs to achieve near-identical or better positional accuracy as a single high-quality sensor to minimize cost, size, weight, and power (C-SWaP) without sacrificing the positional estimation accuracy. The primary focus is on a generalized method to fuse multiple position estimations from multiple co-located IMUs for a single navigating body. The proposed fusion algorithm is applied to simulated data produced by three precision micro-electromechanical systems (MEMS) grade IMU modules (Analog Devices ADIS16465) from two different simulated flight paths. The absolute error is calculated between the position estimation generated by the proposed algorithm and the "truth" position provided by the simulation to determine the accuracy of the final result. The error of the proposed algorithm using the Analog Devices modules is then compared to the error between a single navigational grade IMU (NovAtel IMU-ISA-100 C) and the simulated "truth" position. The results show that using only three precision MEMS grade IMUs; the proposed method can produce identically accurate position estimations as a navigational grade IMU while drastically reducing C-SWaP. This result is further validated in measured data from an instrumented test setup using the above mentioned IMU configurations fused with a standard GPS and compared to a real-time kinematic GNSS setup used as a the third-party ground truth. In addition, the proposed method is further validated by integrating the two navigation systems with a Ku-band radar to produce synthetic aperture radar images. The image produced using the multi-IMU configuration as opposed to the navigation-grade IMU is more focused. Given these results, the proposed method has been validated in theory, simulation, and measurement, resulting in an order of magnitude reduction in cost, size, and power consumption, as well as a three-and-a-half times weight reduction of the overall IMU solution.

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Modification of the line-of-sight motion error for squinted SAR after real-time PRF adjustment

Wang

et al. 2022

J. Phys.: Conf. Ser.

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The motion error of a multi-rotor unmanned aerial vehicle (UAV) leads to severe image blurring for mini synthetic aperture radar (SAR) systems. The along-track displacement error usually is compensated in advance through real-time pulse repetition frequency (PRF) adjustment. And then, only the cross-track displacement error is considered in traditional motion compensation (MOCO) algorithms. However, the instantaneous range expression based on the geometry of a squinted SAR shows that the residual along-track displacement error after PRF adjustment cannot be ignored, especially for mini-SAR systems. Therefore, the line-of-sight (LOS) motion error is modified by introducing the residual along-track displacement error. And then, the first and second-order factors for the LOS MOCO are redefined. The experimental results show that the proposed method can reduce the LOS motion error and significantly improve the imaging performance of the squinted SAR mounted on a multi-rotor UAV.

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An Up-Sampled Particle Filter Fusion Technique and Its Application in Synthetic Aperture Radar Imaging

Cited by 6 publications

References 33 publications

Anchor-Based, Real-Time Motion Compensation for High-Resolution mmWave Radar

Anchor-Based, Real-Time Motion Compensation for High-Resolution mmWave Radar

Reduced Navigation Error Using a Multi-Sensor Fusion Technique and Its Application in Synthetic Aperture Radar

Modification of the line-of-sight motion error for squinted SAR after real-time PRF adjustment

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