• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1025-1033
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• 2004

This paper covers the detection of covert direct sequence spread spectrum signal without the PN(Pseudo Noise) code information. Due to its low probability of interception, the difficulty of spectrum surveillance increases. Detection parameters are the signal existence of given bandwidth, the length of spreading sequence used by transmitter, and the identification of spreading code for detected chip length. The triple correlation function(TCF) value which is one of the higher order statistical signal processing techniques can be used to detect spread spectrum signal without a prior knowledge, but, it has weakness that TCF results depend on the spread data sequence in actual application. This paper proposes the new scheme that not only overcomes the weakness but also presents better performance than the traditional TCF scheme. The performance comparison of conventional TCF with proposed technique shows that the triple correlation estimator(TCE) has better detection capability.

• The Journal of the Acoustical Society of Korea
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• v.16 no.4
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• pp.29-34
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• 1997

The prediction of detection range of a passive sonar system is essential to estimate the performance and to optimize the operation of a developed sonar system. In this paper, a model for the prediction of detection range in a range-dependent ocean environment based on the sonar equation is developed and tested. The prediction model calculates the transmission loss using PE propagation model, signal excess, and the detection probability at each target depth and range. The detection probability is integrated to give the estimated detection range. In order to validate the developed model, two cases are considered. One is the case when target depth is known. The other is the case when the target depth is unknown. The computational results agree well with the previously published results for the range-independent environment. Also,the developed model is applied to the range-dependent ocean environment where the warm eddy exists. The computational results are shown and discussed. The developed model can be used to find the optimal frequency of detection, as well as the optimal search depth for the given range-dependent ocean environment.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.101-111
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• 2023

Many spoofing detection studies have been conducted to cope with the most difficult types of deception among various disturbances of GPS, such as jamming, spoofing, and meaconing. In this paper, we propose a spoofing detection scheme based on elevation masked-relative received power between GPS L1 and L2 signals in a system using a multi-band array antenna. The proposed scheme focuses on enabling spoofing to be normally detected and minimizes the possibility of false detection in an environment where false alarms may occur due to pattern distortion among elements of an array antenna. The pattern distortion weakens the GPS signal strength at low elevation. It becomes confusing to detect a spoofing signal based on the relative power difference between GPS L1 and L2, especially when GPS L2 has weak signal strength. We propose design parameters for the relative power threshold including beamforming gain, the minimum received power difference between L1 and L2, and the patch antenna gain difference between L1 and L2. In addition, in order to eliminate the weak signal strength of GPS L2 in the spoofing detection process, we propose a rotation matrix that sets the elevation mask based on platform coordinates. Array antennas generally do not have high usefulness in commercial areas where receivers are operated alone, but are considered essential in military areas where GPS receivers are used together with signal processing for beamforming in the direction of GPS satellites. Through laboratory and live sky tests using the device under test, the proposed scheme with an elevation mask detects spoofing signals well and reduces the probability of false detection relative to that without the elevation mask.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1997.11a
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• pp.137-146
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• 1997

The simplest bit error detection scheme is to append a parity bit to the end of a bit sequence. In this paper an error correction technique with the use of a parity bit is proposed, and the performance of the proposed system is analyzed. The error probability of the proposed system is compared with the output of computer simulation of the proposed system. It is also compared with the error probability of error at BPSK system, and the signal-to-noise ratio gain is showed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.20-33
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• 2015

Spectrum sensing is a key component of cognitive radio. The prediction of the primary user status in a low signal-to-noise ratio is an important factor in spectrum sensing. However, because of noise uncertainty, secondary users have difficulty distinguishing between the primary signal and an unauthorized signal when an unauthorized user exists in a cognitive radio network. To resolve the sensitivity to the noise uncertainty problem, we propose an entropy-based spectrum sensing scheme to detect the primary signal accurately in the presence of an unauthorized signal. The proposed spectrum sensing uses the conditional entropy between the primary signal and the unauthorized signal. The ability to detect the primary signal is thus robust against noise uncertainty, which leads to superior sensing performance in a low signal-to-noise ratio. Simulation results show that the proposed spectrum sensing scheme outperforms the conventional entropy-based spectrum sensing schemes in terms of the primary user detection probability.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.285-289
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• 2009

In this paper, we propose a novel double-talk detection (DTD) technique based on soft decision in the frequency domain. In the proposed method, global near-end speech presence probability (GNSPP) considering the statistical model assumption and voice activity detection (VAD) decision of the near-end and far-end signal are applied to the DTD algorithm in the frequency domain instead of the traditional hard decision scheme using cross-correlation coefficients. The performance of the proposed algorithm is evaluated by the objective test under various environments, and yields better results compared with the conventional scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2C
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• pp.238-245
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• 2010

For orthogonal frequency division multiplexing (OFDM) systems sharing the spectrum with narrow band primary devices, a fractional bandwidth (FBW) mode has been proposed recently to reduce the interference to the primary users. The FBW mode divides the total OFDM bandwidth into subbands and activates (or deactivates) a subset of the subbands according to the result of spectrum sensing. In this paper, we analyze the detection error probability of FBW mode information which is delivered by the sequence embedded in the preamble and evaluate the performance in wireless regional area network environments. The results show that the detection probability derived analytically estimates the actual value from simulation adequately and that a low detection error probability less than $10^{-3}$ is obtained at a low signal-to-noise power ratio.

• Phonetics and Speech Sciences
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• v.2 no.3
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• pp.141-148
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• 2010

In this paper, voice activity detection (VAD) for dual-channel noisy speech recognition is proposed in which spatial cues are employed. In the proposed method, a probability model for speech presence/absence is constructed using spatial cues obtained from dual-channel input signal, and a speech activity interval is detected through this probability model. In particular, spatial cues are composed of interaural time differences and interaural level differences of dual-channel speech signals, and the probability model for speech presence/absence is based on a Gaussian kernel density. In order to evaluate the performance of the proposed VAD method, speech recognition is performed for speech segments that only include speech intervals detected by the proposed VAD method. The performance of the proposed method is compared with those of several methods such as an SNR-based method, a direction of arrival (DOA) based method, and a phase vector based method. It is shown from the speech recognition experiments that the proposed method outperforms conventional methods by providing relative word error rates reductions of 11.68%, 41.92%, and 10.15% compared with SNR-based, DOA-based, and phase vector based method, respectively.

• Journal of information and communication convergence engineering
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• v.13 no.4
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• pp.241-247
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• 2015

Cognitive radio has been attracting increased attention as an effective approach to improving spectrum efficiency. One component of cognitive radio, spectrum sensing, has an important relationship with the performance of cognitive radio. In this paper, after a summary and analysis of the existing spectrum-sensing algorithms, we report that the existing eigenvalue-based semi-blind detection algorithm and blind detection algorithm have not made full use of the eigenvalues of the received signals. Applying multi-antenna systems to cognitive users, we design a variety of spectrum-sensing algorithms based on the joint distribution of the eigenvalues of the received signal. Simulation results validate that the proposed algorithms in this paper are able to detect whether the signal of the primary user exists or not with high probability of detection in an environment with a low signal-to-noise ratio. Compared with traditional algorithms, the new algorithms have the advantages of high detection performance and strong robustness

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12C
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• pp.1082-1087
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• 2008

Maximum Likelihood (ML) detection is well known to exhibit better bit-error-rate (BER) than many other detectors for multiple-input multiple-output (MIMO) channel. However, ML detection has been shown a difficult problem due to its NP-hard problem. It means that there is no known algorithm which can find the optimal solution in polynomial-time. In this paper, Semi-Definite relaxation (SDR) is iteratively applied to ML detection problem. The probability distribution can be obtained by survival eigenvector out of the dominant eigenvalue term of the optimal solution. The probability distribution which is yielded by SDR is recurred to the received signal. Our approach can reach to nearly ML performance.