Enhance LFMCW radar detection and complexity using adaptive recovery CAMP algorithm

Hossiny, M. H.; Salem, Sameh G.; Ahmed, Fathy M.; Moustafa, K. H.

doi:10.1109/iwdrl.2018.8358207

Cited by 8 publications

(4 citation statements)

References 7 publications

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“…Instead of decoding directly based on Equation 8, this problem is solved based on an ACAMP algorithm. 31 The proposed adaptive recovery algorithm is used for LFMCW and pulsed radar detection enhancement with an approximately good result as in. 32 The adaptive algorithm is mainly dependent on the phase changing as in Equation 10.…”

Section: The Proposed Acamp Based On Compressive Measurementsmentioning

confidence: 99%

“…Even if η can be estimated based on the current state and the previous accumulated phase, the problem of error propagation still needs to be addressed. Instead of decoding directly based on Equation , this problem is solved based on an ACAMP algorithm 31 . The proposed adaptive recovery algorithm is used for LFMCW and pulsed radar detection enhancement with an approximately good result as in 32 .…”

Section: The Proposed Acamp Based On Compressive Measurementsmentioning

confidence: 99%

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Decoding and measurement of frequency‐hopping spread spectrum signals using an adaptive algorithm‐based compressive sensing

Ghanem¹

2020

Int J Communication

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Summary Decoding of frequency‐hopping spread spectrum (FHSS) methods to intercept the symbol content in signals and brilliant measurement is presented in this paper. The switching of the frequency channels rapidly using a pseudorandom code makes interception of FHSS signals very difficult. Therefore, a proposed adaptive compressive measurement for decoding the frequency‐hopping receivers that have no prior knowledge of the hopping sequence is the main focus of this work. The proposed methods rely on the instantaneous sparsity of the spectra of FHSS signals, and the transmitted symbols can be recovered from the proposed compressive measurements. Furthermore, the contribution of this work is the design of a proposed adaptive method that is used to design measurement kernels for compressive measurement and decoding based on knowledge enhancement, which includes both prior information enhanced and adaptive methods based on the properties of the intersignals. Simulation results on Gaussian frequency‐shift keying (GFSK) FHSS signals illustrate that the proposed compressive method enhances the detection performance of the received frequencies with acceptable decoding accuracy compared with other techniques such as enhanced orthogonal matching pursuit (EOMP) and an adaptive sampling kernels method with a random compressive ratio. Also, an enhancement of the proposed algorithm is achieved due to enhancement in both the normalized mean square error (NMSE) and the probability of correction error (Pce). The comparison between these algorithms is performed using simulation based on MATLAB and receiver operating characteristic (ROC) curves.

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Section: The Proposed Acamp Based On Compressive Measurementsmentioning

confidence: 99%

Section: The Proposed Acamp Based On Compressive Measurementsmentioning

confidence: 99%

Decoding and measurement of frequency‐hopping spread spectrum signals using an adaptive algorithm‐based compressive sensing

Ghanem¹

2020

Int J Communication

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“…In [4], the authors investigate the real time implementation of the proposed algorithm for LFMCW radar. An enhancement of target detection in both range and Doppler directions based on CS is shown in [5]. In [6], the author enhances the detection of slow Doppler frequencies based on frequency response of both SDLC and integrator.…”

Section: Introductionmentioning

confidence: 99%

Peer Review #2 of "Enhancement of small doppler frequencies detection for LFMCW radar (v0.1)"

2021

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Radars is the main task of this paper. Moving Target Indicator (MTI) is used to reject the fixed targets and high-speed targets through the radar research area. In this work, targets with small Doppler frequencies can be detected perfectly based on the frequency response of Single Delay Line Canceller (SDLC) followed by Single Delay Line Integrator (SDLI). An enhancement of the proposed algorithm is achieved using a filter in the range direction of the range-Doppler processor scheme. The proposed filter is chosen with certain coefficients after the first Fast Fourier Transform (FFT) processor in range to enhance the radar performance. The evaluation of the proposed algorithm is achieved at different slow Doppler scenarios of the target and compared with the traditional algorithm which uses only MTI processor. Another aspect that is important for evaluation of the proposed algorithm is the detection performance of the algorithms through the Receiver Operating Characteristic (ROC) curves. Implementation of the proposed algorithm using FPGA is performed in real time applications and it is found that it meets the simulation results.

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“…In Salem et al (2016), the authors investigate the real time implementation of the proposed algorithm for LFMCW radar. An enhancement of target detection in both range and Doppler directions based on CS is shown in Hossiny et al (2018). In Ahmed (2019), the author enhances the detection of slow Doppler frequencies based on frequency response of both the single delay line canceller (SDLC) and integrator.…”

Section: Introductionmentioning

confidence: 99%

Enhancement of small doppler frequencies detection for LFMCW radar

Ghanem¹

2021

PeerJ Computer Science

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Detection of targets with small Doppler frequencies of linear-frequency modulated continuous wave radars is the main task of this article. The moving target indicator (MTI) is used to reject the fixed targets and high-speed targets through the radar research area. In this work, targets with small Doppler frequencies can be detected perfectly based on the frequency response of a single delay line canceller followed by single delay line integrator. An enhancement of the proposed algorithm is achieved using a filter in the range direction of the range-Doppler processor scheme. The proposed filter is chosen with certain coefficients after the first fast Fourier transform processor in range to enhance the radar performance. The evaluation of the proposed algorithm is achieved at different slow Doppler scenarios of the target and compared with the traditional algorithm which uses only MTI processor. Another aspect that is important for evaluation of the proposed algorithm is the detection performance of the algorithms through the receiver operating characteristic curves. Implementation of the proposed algorithm using FPGA is performed in real time applications and it is found that it meets the simulation results.

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Enhance LFMCW radar detection and complexity using adaptive recovery CAMP algorithm

Cited by 8 publications

References 7 publications

Decoding and measurement of frequency‐hopping spread spectrum signals using an adaptive algorithm‐based compressive sensing

Decoding and measurement of frequency‐hopping spread spectrum signals using an adaptive algorithm‐based compressive sensing

Peer Review #2 of "Enhancement of small doppler frequencies detection for LFMCW radar (v0.1)"

Enhancement of small doppler frequencies detection for LFMCW radar

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