A novel approach to generate OFDM radar signals

Raghavendra, C. G.; Bhat, K. N.; Srivastsa, M. P. Raghu; Murthy, Rahul N; Nayak, P. Vignesh; Prasad, N. N. S. S. R. K.

doi:10.1109/iceeccot.2016.7955203

Cited by 6 publications

(3 citation statements)

References 7 publications

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“…In recent years, with the development of MIMO radar, there has been an increasing number of studies on designing OFDM waveform sets for MIMO radar systems. According to the different sub-carriers, the MIMO radar OFDM waveform sets are divided into two categories: LFM-OFDM [15][16][17][18][19][20] and PC-OFDM [21][22][23][24][25]. The sub-carrier of the LFM-OFDM waveform set is a chirp signal, and thus, the LFM-OFDM waveform set has better Doppler tolerance.…”

Section: Signal M Echomentioning

confidence: 99%

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Low Correlation Interference OFDM-NLFM Waveform Design for MIMO Radar Based on Alternating Optimization

Liu

Sun

et al. 2021

Sensors

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The OFDM chirp signal is suitable for MIMO radar applications due to its large time-bandwidth product, constant time-domain, and almost constant frequency-domain modulus. Particularly, by introducing the time-frequency structure of the non-linear frequency modulation (NLFM) signal into the design of an OFDM chirp waveform, a new OFDM-NLFM waveform with low peak auto-correlation sidelobe ratio (PASR) and peak cross-correlation ratio (PCCR) is obtained. IN-OFDM is the OFDM-NLFM waveform set currently with the lowest PASR and PCCR. Here we construct the optimization model of the OFDM-NLFM waveform set with the objective function being the maximum of the PASR and PCCR. Further, this paper proposes an OFDM-NLFM waveform set design algorithm inspired by alternating optimization. We implement the proposed algorithm by the alternate execution of two sub-algorithms. First, we keep both the sub-chirp sequence code matrix and sub-chirp rate plus and minus (PM) code matrix unchanged and use the particle swarm optimization (PSO) algorithm to obtain the optimal parameters of the NLFM signal’s time-frequency structure (NLFM parameters). Next, we keep current optimal NLFM parameters unchanged, and optimize the sub-chirp sequence code matrix and sub-chirp rate PM code matrix using the block coordinate descent (BCD) algorithm. The above two sub-algorithms are alternately executed until the objective function converges to the optimal solution. The results show that the PASR and PCCR of the obtained OFDM-NLFM waveform set are about 5 dB lower than that of the IN-OFDM.

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Section: Signal M Echomentioning

confidence: 99%

“…Ω is the solution space. X is an optimization variable satisfying the constraint conditions in Equation (23). 0 represents the mapping from the solution space Ω to the space of piecewise chirp signal.…”

Section: Ofdm-nlfm Waveform Set Optimization Modelmentioning

confidence: 99%

Low Correlation Interference OFDM-NLFM Waveform Design for MIMO Radar Based on Alternating Optimization

Liu

Sun

et al. 2021

Sensors

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“…Modern RF synthesis techniques and digital signal processing resources provide radar waveform designers the opportunity for developing increasingly complex waveforms to meet radar system requirements. Examples of these types of waveforms include multi-frequency carrier OFDM [5][6][7], combined LFM/Barker codes [8,9] and combined LFM/PRN phase codes [10,11]. Traditional radar applications for these type of complex waveforms include marine radar [11], synthetic aperture radar (SAR) [12] and collision avoidance radar [13].…”

Section: Introductionmentioning

confidence: 99%

Design of a Short Range Continuous Wave Compound Phase Coded Linear Frequency Modulation Radar Sensor

Reneau¹,

Adhami²

2018

PIER B

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The design of a low cost, short range radar sensor based upon a novel phase coded linear frequency waveform is discussed in this paper. The radar sensor utilizes a novel waveform that is produced using digital frequency synthesis techniques. Digital frequency synthesis techniques enable the generation of repeatable, highly linear frequency sweeps and provide a means for accurate application of phase codes to linear frequency modulations. The work presented contains analysis of the component linear frequency and phase code modulations that form the compound phase coded linear frequency modulation. The resulting compound phase coded linear frequency modulation is compared with the component modulations to demonstrate the performance improvement that can be achieved by the combining of radar waveform modulations enabled by modern digital frequency synthesis techniques. The compound phase coded linear frequency modulation waveform shows improved range resolution and suppression of range sidelobes over the individual component waveforms. The phase coded linear frequency modulation shows an improvement of 13 dB over the linear frequency modulation and is only 2 dB less than the phase code. It also achieves a 5 and 10 nanosecond narrower mainlobe autocorrelation peak than the phase code and linear frequency modulation, respectively. A notional signal processing architecture of the waveform is simulated to demonstrate the ability to process the compound waveform. Experimental data collected from a direct digital frequency synthesis based arbitrary waveform generator is compared with the simulated waveform. The compound waveform model and the experimental results show good agreement.

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Reduction of Sidelobe Levels in OFDM Radar Signal Using Two Samples Sliding Window Adder (TSSWA) Algorithm

Srivatsa

Raghavendra

2021

Advances in Intelligent Systems and Computing

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A novel approach to generate OFDM radar signals

Cited by 6 publications

References 7 publications

Low Correlation Interference OFDM-NLFM Waveform Design for MIMO Radar Based on Alternating Optimization

Low Correlation Interference OFDM-NLFM Waveform Design for MIMO Radar Based on Alternating Optimization

Design of a Short Range Continuous Wave Compound Phase Coded Linear Frequency Modulation Radar Sensor

Reduction of Sidelobe Levels in OFDM Radar Signal Using Two Samples Sliding Window Adder (TSSWA) Algorithm

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