This paper presents the author''s research results for heterogeneous channel error correction on phase array antennas in Global Navigation Satellite System in order to improve noise quality for terminals. The error correction method proposed by the author is a two-stage algorithm with automatic correction and error correction algorithm based on self-compensation.
Research PROPOSED METHODS FOR HETEROGENEOUS ERROR CORRECTION OF RECEIVE CHANNEL FOR GNSS ANTI-INTERFERENCE DEVICES Ngo Xuan Mai1*, Phung Quang Thanh2, Hoang The Khanh3, Nguyen Huy Hoang4 Abstract: This paper presents the author's research results for heterogeneous channel error correction on phase array antennas in Global Navigation Satellite System in order to improve noise quality for terminals The error correction method proposed by the author is a two-stage algorithm with automatic correction and error correction algorithm based on self-compensation Keywords: Heterogeneity on phase array antenna reception channel; Anti-jamming GNSS; Group delay INTRODUCTION Currently, Global Navigation Satellite Systems (GNSS) play an increasingly important role in all key sectors of both civil, industrial and national security However, signals from satellites positioned to receiver inputs are greatly reduced by many objective and subjective factors Therefore, the studies on improving quality of receivers have been and continues to be attracted by many domestic and international researchers Solutions using phased array antennas have been widely applied However, one of the technical problems when processing signals on phase array antennas is the heterogeneity between receiving channels This is an unavoidable problem due to the fact that the same phase rotators cannot be produced The heterogeneity on the adaptive phase array antenna receiver channel is represented by the initial phase fluctuations of oscillations, bandwidth fluctuations and the difference in receiver-amplitude-frequency characteristics These factors have a great influence on the anti-interference quality for the terminals in GNSSs In order to overcome the effect of this heterogeneity, it is necessary to design a multichannel anti- interference filter by employing heterogeneous error correction function In this paper, the author proposes two heterogeneous error correction algorithms on receiver channel: A two-phase algorithm with automatic error correction and a heterogeneous error correction algorithm based on self-compensation These algorithms are built based on Frost algorithm with the minimization of signal output over antenna output This paper consists of four parts: part of the paper raises the question, part presents the theoretical analysis of the channel error correction methods using a two-stage algorithm based on automatic correction and using heterogeneous error correction algorithm based on self-compensation, part shows the results of simulation together with the evaluation of results, part concludes the article and proposes next research direction THEORY 2.1 Method of heterogeneous channel error correction in two stages based on automatic error correction 2.1.1 System model The structure of the two-stage filter is shown in Figure in which SF - space filter, TF - time filter The anti-jamming process establishes the minimum point of direction diagram towards the noise source and the peak of schema towards the signal source by adjusting a time weighting vector KTi , i 1, M The heterogeneous error correction of receiver channels is then performed by adjusting the space weighting vector VijT vector, Journal of Military Science and Technology, Special Issue, No.60A, 05 - 2019 Electronics & Automation i 1, M , j N The Filter works in modes: automatic error correction and operational mode Fig The two-stage filter structure with automatic error correction The correction is performed for a period of time determined by the time stability of the adaptive phase array antenna receivers According to the test signal, it produces a uniform spectrum within the processing range The test signal may be white noise transmitted through a bandpass filter with linear frequency response and phase response An important feature of the proposed method is that during the time of error correction, it takes place not only in correcting the amplitude-frequency and phase-frequency characteristics of the receiver channels but also eliminating the test signal and useful signals (if it does not coincide with the azimuth of the test signal) transmitted to the output Thus, the automatic error correction filter suitable for signal transmission is useful in continuous mode The output of filter is expressed as: M N i 1 j 1 y n ki (n ) vij x n j 1 (1) Where N is the number of time branches, M is the number of receiver channels, n is discrete time, ki , vij are the elements corresponding to the weight vector of space – time process x i (n ) is vector of the input signal and noise Let consider the stage of signal processing space as a separate case of time space processing when vij (n ) const , then the expression (1) will be rewritten in vector form n T as y(n ) X W Where XT is the class vector of the input signal and noise: N X Mai, …, N H Hoang, “Proposed methods for … GNSS anti-interference devices.” Research XT XT1 XTj XTN , j 1, N , XTj x j x ji x jM , i 1, M , W is the column vector of weights with elements wij ki vij : WT W1T WjT WNT , j 1, N , WjT w j w ji w jM , i 1, M The result is W V K where is the product of vectors by each element When using high-power broadband signal as a test signal as shown above, it is clear that the automatic balance of the filter channels will be meaningful if the processing power at the filter output is minimized By optimizing the general adaptation of all coefficients wij while still complying with the same conditions, then the calibration error is optimized If it is ensured that the test signals being at the input of channels has the same initial phase and ki 1, i M then the channels will be aligned to the original phase At this stage, it is possible to use any adaptive criterion to adjust the weight ki when vij (n ) const ; in particular, the standard for minimum output power not accompanied by a useful signal is similar The initial weight vector ( N M ,1 ) is in the form: W0 CST (CTST CST )1b1 In the case b1 , the directional schema of the initial antenna is isotropic To prevent space-time interference, CTST [CT1 CT2 the limit matrix CTST is represented in the form: CTj CTN ] , with N is the number of branches of the filter of finite pulse characteristics in each antenna channel, and the component vectors C j in the limit can be determined from necessary space-frequency limits The adaptation of the weight vector of time filter is carried out in the loop number p , and the weight vector adaptive of the space filter is performed in loop number q , and the process is then repeated + Signal space processing stage (auto error correction stage) Step 1: The signal at the output of the interferer is represented by the following matrix: K(1) y(1) X(1)T (V(1) K(1) N (2) where K is the weight vector used for the space filter: Journal of Military Science and Technology, Special Issue, No.60A, 05 - 2019 Electronics & Automation k 1 K , kM At this step, K(1) is the unit vector Hence, V(1) W(1) We can rewrite the formula (2) in the form: (3) y(1) WT (1)X(1) , p equivalent to the average calculation in the period of the corresponding period or in the period p T seconds and T is the sampling period Step r q : The signal at the output of the interferer is represented by the following matrix: K(r ) y(r ) X(r )T (V(r ) (4) K(r ) N At this step, K(r ) is the unit vector Hence, V(r ) W(r ) We can rewrite (4) in R(1) (1 )R(0) X* (1)XT (1) , with R(0) , and the parameter the form: y(r ) WT (r )X(r ) The correlation matrix is shown corresponding to the calculation according to the formula: R(r ) (1 )R(r 1) X* (r )XT (r ) + Operation stages Step q : The signal at the output of the interferer is represented by the following matrix: (5) y(q 1) ZT (q 1)K(q 1) With Z(r ) , ViT (q 1) are respectively the output signal and the coefficients of the time filter on the channel i at step q The weight vector in formula (5) can be calculated according to the formula: K(q 1) P[K1 (q ) z R zz K1(q )] K0 For which the initial weight vector can be defined as K0 1 0 , z and calculated as the own value of the matrix R zz (q 1) , or as / diag(R zz (q 1)) R zz (q 1) (1 )R zz (q ) Z* (q 1)ZT (q 1) , với R zz (q ) Step r q q p : The signal at the output of the interferer is represented by the following matrix: y(r ) ZT (r )K(r ) At this step, the time coefficients are not changed, therefore V(r ) V(q 1) V(q ) , Hence K(r ) P[K1(r 1) z R zz K1(r 1)] K0 10 N X Mai, …, N H Hoang, “Proposed methods for … GNSS anti-interference devices.” Research where z is defined as the maximum specific value of the matrix R zz (r ) , or in the form / diag(R zz (r )) , R zz (r ) (1 )R zz (r 1) Z* (r )ZT (r ) Step p q 1 2q p : Output signal and weight vector can be calculated as in the step: r q Step: 2q 2p 1 3q 2p The output signal and weight vector are calculated as at steps: r q q p The process continues so on 2.1.2 Evaluation of simulation results Computer simulation on MATLAB environment is performed for the case p 50000 , q 50000 with signal and noise conditions as follows: Scenario 1: There is a broadband noise operating on the horizontal plane with a relative power of 40dB The noise is unstable (noise spectrum width of 60000 initial 16Mhz time samples, noise spectrum width of 65000 time samples after 8Mhz) Scenario 2: There is a broadband noise operation on the horizontal plane with the relative capacity of 40dB Sample signal is used for the comparison selection with 8MHz band Unstable noise (the noise spectrum of the original 60000 time samples is MHz and the noise spectrum of the time samples from 60001 to 125000 is 16Mhz) Scenario 3: A sample signal of 40dB wide range is transmitted for time samples from to 50000 and from 100001 and the azimuth of the sample signal source is 00 There is broadband noise operating on the horizontal plane with public 40dB relative power The spectral width of noise is 16Mhz and the noise emitter is turned on starting from the 50001 to 100000 time samples and the noise source is 900 Scenario 4: There are broadband noise distributions as in the previous section Sample signal for comparison is selected within 8Mhz range The noise is unstable (the width of the interference spectrum to the 60000 time sample is 8Mhz with the noise spectrum of 65,000 samples after 16Mhz) a Case of homogeneous receiver channel For the case of a homogeneous channel, A number of typical situations for a disturbance such as situations 1,2,3 and the situation where there are broad-band noise such as the situation is simulated In order to conduct basic comparison, the evaluation with simulation results for case of receiver channel is heterogeneous (a) (b) Scenario Journal of Military Science and Technology, Special Issue, No.60A, 05 - 2019 11 Electronics & Automation (a) (b) Scenario interference compression ratio 90 SINR output Ratio -10 (1) 80 -15 (4) 70 (4) (2) -20 (3) 60 -25 -30 (3) 40 dB dB 50 (1) 30 (1) -45 (1) Two stages algorithm - Appelbaum (1) Two stages algorithm - Frost (2) STAP - Appelbaum (3) STAP - Frost (4) 10 (4) (4) -40 (2) 20 (2) (3) -35 Two Statges algorithm - Appelbaum (1) Two Statges algorithm - Frost (2) STAP algorithm - Appelbaum (3) STAP algorithm - Frost (4) -50 -55 -10 -60 10 12 10 calculation steps 10 (a) 12 10 calculation steps (b) Scenario interference compression ratio 60 SINR output Ratio (4) (2) 50 -10 40 (4) -20 (2) (3) (3) dB dB 30 -30 (1) 20 -40 (1) 10 Two stages algorithm - Appelbaum (1) Two stages algorithm - Frost (2) STAP algorithm - Appelbaum (3) STAP algorithm -Frost (4) Two Statges algorithm - Appelbaum (1) Two Statges algorithm - Frost (2) STAP algorithm - Appelbaum (3) STAP algorithm -Frost (4) -50 -10 -60 calculation steps 10 12 10 (a) calculation steps 10 12 10 (b) Scenario Fig Interference compression ratio (a) and output SINR ratio (b) - homogeneous b Case of heterogeneous receiver channel Where the receiver channel is heterogeneous and the filter order number is Heterogeneous characteristics of the channels are as follows: amplitude of the initial phase, amplitude-frequency characteristics, bandwidth of the Mid-range amplifier filter in 12 N X Mai, …, N H Hoang, “Proposed methods for … GNSS anti-interference devices.” Research receiver channels are 50, 0.5dB, 200kHz, respectively The correlation interval is heterogeneous and the frequency response of the mid-frequency amplifier filters is Mhz The results are simulated for the signal and noise case with the assumption similar to the Scenarios 1,2,3,4 above: interference compression ratio 40 (2) (1) 35 30 25 (4) dB 20 (4) (3) (4) (3) 15 (2) 10 Two stages algorithm - Appelbaum (1) Two stages algorithm - Frost (2) STAP - Appelbaum (3) STAP - Frost (4) -5 -10 10 12 10 calculation steps (a) (b) Scenario interference compression ratio 40 (4) (3) 35 SINR output Ratio -15 (4) (2) (2) -20 30 -25 25 (2) (1) (3) -30 (2) 20 (3) (4) 15 (2) -40 (1) 10 (1) dB dB -35 (4) (3) -45 -5 -55 -10 (1) Two Statges algorithm - Appelbaum (1) Two Statges algorithm - Frost (2) STAP algorithm - Appelbaum (3) STAP algorithm -Frost (4) -50 Two stages algorithm - Appelbaum (1) Two stages algorithm - Frost (2) STAP - Appelbaum (3) STAP - Frost (4) -60 10 12 10 calculation steps 10 12 10 calculation steps (a) (b) Scenario interference compression ratio SINR output Ratio 35 30 -20 25 (4) 15 (1) (2) (2) (3) (4) (3) (4) -40 (1) dB 10 dB -30 (3) 20 (2) (1) -50 (2) (1) (4) (3) -60 -5 Two stages algorithm - Appelbaum (1) Two stages algorithm - Frost (2) STAP - Appelbaum (3) STAP - Frost (4) -10 -15 -20 calculation steps Two Statges algorithm - Appelbaum (1) Two Statges algorithm - Frost (2) STAP algorithm - Appelbaum (3) STAP algorithm -Frost (4) -70 10 12 -80 10 (a) calculation steps 10 12 10 (b) Scenario Journal of Military Science and Technology, Special Issue, No.60A, 05 - 2019 13 Electronics & Automation interference compression ratio 35 (2) 30 SINR output Ratio -10 (2) -15 -20 25 (2) 20 (4) (1) -25 (3) (2) -30 (1) dB dB 15 10 (4) (3) (2) (3) -35 (1) (4) (4) -40 (3) (4) -45 Thuat toan hai giai doan - Appelbaum Thuat toan hai giai doan - Frost Xu ly khong gian - Appelbaum Xu ly khong gian - Frost -5 Two stages algorithm - Appelbaum (1) Two stages algorithm - Frost (2) STAP algorithm - Appelbaum (3) STAP algorithm -Frost (4) -50 -55 -10 -60 calculation steps 10 12 10 4 10 calculation steps 12 10 (a) (b) Scenario Fig Interference compression ratio (a) and output SINR ratio – heterogeneous case 2.2 Method of heterogeneous channel error correction based on self-compensating blocks In the proposed algorithm above, although the anti-interference characteristics are better than even when the channel was homogeneous and when the channel loses its consistency and instability It is still possible to see that there is still specific deterioration of anti-interference Although this declines in very short time, for devices that require high frequency of information updates (e.g devices moving at high speeds), this reduction range can cause the loss of information control Therefore, the author proposes the heterogeneous channel error correction algorithm based on self-compensating blocks 2.2.1 System model The filter structure for correcting the heterogeneity of receiver channel based on selfcompensation is described in Fig Fig Filter structure corrects heterogeneity receiver channel based on selfcompensation 14 N X Mai, …, N H Hoang, “Proposed methods for … GNSS anti-interference devices.” Research The output of this filter is described by the expression (6) as following M K y n x n k 1 wmk (6) m 1 k 1 The mixtures of input signals are described by following expressions H W0 XT W XT W WH X* XT W WH R W W W W (7) With the automatic compensation of all coefficients in the first channel (standard channel) which are equal to 1; hence, the weight vector for an M element antenna is represented in the form: WT 1 w M wMk wMN Where k N , N is the number of time branches of the filter with finite pulse characteristics Limit vector CT and initial weight vector for automatic compensation are given by formula (1.8) and (1.9): T C (0) 1 0 N (8) T W (0) 1 0 N (9) Where N is the number of time branches of the filter with finite pulse characteristics 2.2.2 Evaluation of simulation results The anti-interference characteristics are calculated in the case of time branches with automatic compensation blocks on channels The sample signal of broad-band noise (16MHz) is used The conditions of noise and signal are assumed as follows: Direction of the satellite signal is (00,00), the value in the first position is the azimuth in the second position the offset angle Relative power of useful signal is -20dB (from individual noise in the processing range) The relative total power (from individual noise in the processing range) of broad-band noise is 40dB and all sources have the same power The direction of interference sources is: Scenario 1: offset angles = [850 750 800 450 820 600] and azimuths are evenly distributed Scenario 2: all noise on the horizontal plane and the azimuth is evenly distributed Sampling frequency is 25 MHz; transmission bandwidth is 16 Mhz Journal of Military Science and Technology, Special Issue, No.60A, 05 - 2019 15 Electronics & Automation The dependence of the interference compression ratio over the number of broad-band noise sources 80 The dependence of SINR ratio over the number of broad-band noise sources -5 70 -10 60 -15 50 -20 40 -25 30 -30 Scenario - self-compensating Scenario - self-compensating Scenario Scenario 20 Scenario - self-compensating Scenario - self-compensating Scenario Scenario -35 10 -40 Number of broad-band noise sources Number of broad-band noise sources (a) (b) Fig The dependence of the interference compression ratio (a) and the SINR ratio at the output (b) over the number of broad-band noise sources The dependence of the interference compression ratio over the number of broad-band noise sources 35 The dependence of SINR ratio over the number of broad-band noise sources -15 30 dB -20 25 -25 20 -30 Scenario - self-compensating Scenario - self-compensating Scenario Scenario 15 Scenario - self-compensating Scenario - self-compensating Scenario Scenario -35 10 Number of broad-band noise sources Number of broad-band noise sources (а) (b) Fig The dependence of the interference compression ratio (a) and the output SINR ratio (b) over the number of broad-band noise sources In Figures and 4, the interference compression ratio and the SINR ratio are valued for the self-compensator where Frost algorithm is applied The distance between elements is d 2 / 3.56 with solid lines representing the symbol of automatic compensator and the dashed lines for STAP algorithm without compensation 2.3 Evaluation of the non-working zone of GNSS receivers To assess the non-working zone of receiver using the two proposed algorithms above, the non-working zone simulation of the GNSS receiver for cases of phase distortion, amplitude distortion or both phase distortion and amplitude distortion and the use of two proposed algorithms are stimulated to correct heterogeneous errors on the receiver channel with the effect of broad-band noise sources for 7-element array phase antenna with the distance between antenna elements as d 2 / 3, 56 By looking at Fig 7, the curve of the non-working zone dependency on the receiver's protection ratio using the two-stage algorithm shows better error correction than the selfcompensating algorithm The curve of non-working zone using both proposed algorithms is asymptotic to the curve of non-working zone where the receiver channel is homogeneous and is significantly better than the curves where the channel is heterogeneous (red, pink and blue lines, respectively) Therefore, we may conclude that 16 N X Mai, …, N H Hoang, “Proposed methods for … GNSS anti-interference devices.” Research the two proposed algorithms are fully efficient even when the channel has heterogeneity in both phase and amplitude Fig Comparison of non-working zone dependencies to the GNSS receiver ratio when using two proposed algorithms EVALUATION OF SIMULATION RESULTS AND DISCUSSION On Figures and 3, the Figures represent the dependence of the interference compression ratio and the SINR ratio on the number of calculation steps when using a two-stage algorithm with automatic error correction and the processing algorithms signal space is not corrected when the channel is homogeneous (Figure 2) and heterogeneous (Figure 3) in a number of different signal and noise conditions Based on the results in Figure 2, in case the channel is homogeneous, the two-stage self-correction algorithm proposed by the author still works well although there are several points where the anti-interference characteristics are greatly reduced The results are then compared with those when the receiver channels on phase array antennas are heterogeneous using the original algorithm published in [12] It can be seen that the antiinterference characteristics when applying a two-phase calibration algorithm are better than the original algorithm for Frost algorithm in most signal and noise conditions Especially, the gain in SINR ratio on output is significantly superior As for Appelbaum algorithm, the anti-interference characteristics of the two-stage algorithm have been corrected or better in some situations (situations 1,2,3) and got worse in situations For static disturbances when changing from the adjustment stage (from step 1-50000) to the operating phase (the calculation steps from 50001-100000), the compression ratio and the actual SINR ratio not change This rule is true for both homogeneous channels and heterogeneous channels (Figures and 3) For homogenous and heterogeneous channels where the number of noise sources increases, the SINR ratio increases to dB This is explained by the computational arrangement of the direction of noise chosen during the time the formation of the "0" direction is bulged in the direction of the peak in the place with satellite's useful signal (situations 1, 2, 4) For homogeneous and heterogeneous channels when the relative power reduction of noise interference ratio is reduced, the output SINR ratio increases because the input SINR ratio also increases (Scenarios 1, 2, 4) Journal of Military Science and Technology, Special Issue, No.60A, 05 - 2019 17 Electronics & Automation For homogeneous and heterogeneous channels when the noise is unstable with the narrowing of their range at the time of changing the frequency band, the SINR ratio of the two-step algorithm follows to the minimum The power increase (0.3 dB) is negligible because the original algorithm is effective while the remaining algorithms increase significantly (2 dB ÷ 12 dB) (as in situation where the change in frequency band takes place at sample time 60001) For homogeneous and heterogeneous channels when the noise is unstable with their widened range (in the 60001th time sample) the SINR of all algorithms will be reduced ( 0.5dB 17dB , respectively) At the next correction stage (100001 samples) the SINR ratio is restored (situation (b), situation (b)) The two-stage algorithm has the advantage in which its SINR ratio is reduced by 2dB being smaller than those in other algorithms For homogeneous and heterogeneous channels when unstable noise appears, a characteristic "drop" of 40dB (in the 60001 time sample) of all algorithms, in the next working phase, is greatly restored This phenomenon confirms the effectiveness of the calibration method when the sample signal does not match the direction of noise In Figures and 6, the value of the interference compression ratio and the SINR ratio for the compensator is presented when applying Frost algorithm The distance between elements is d 2 / 3.56 , where solid line shows the symbol of automatic compensator and the dashed lines are for STAP algorithm without compensation For the case of heterogeneous receiver channels, the automatic compensator is calibrated depending on the noise condition and the interference compression ratio will be less than that of the corrected STAP algorithm of 3.5 7.5dB , and the SINR ratio output is worse at 5.5dB ; however, it helps protect the device to locate the user because its compression coefficient characteristics are no less than the minimum allowance When the numbers of broad-band noise sources are from ÷ 6, the interference compression ratio and the SINR ratio output for the 1st noise distribution match the case of 2nd statement as well as in the case of heterogeneous channels When the number of noise sources exceeds the number of degrees of freedom of the antenna array, namely noise for the second case, the noise power compression coefficient is greater than the value 18dB in first case When the number of broad-band noise sources is 4, the SINR ratio is greater than the output for the 2nd case and better than the value 15dB in the first case CONCLUSION The heterogeneous error correction algorithms of receiver channels on adaptive phase array antennas have been studied and proposed Through simulation results and analysis of different signals and noise scenarios, the proposed methods are highly effective When applying a two-stage self-correction error correction method for adaptive phase array antennas of elements in a homogeneous channel case, the SINR ratio varies from 10dB 16dB ; while the channel is heterogeneous, the correction is 11.5 21dB As the most effective automatic compensation method for Frost algorithm, it allows anti-interference when the heterogeneity of adaptive phase array antenna receivers is high and in highly unstable conditions of receiver Applying the automatic compensation method helps improve the SINR ratio at the magnetic output at 1.5 16dB and improve the magnetic noise power compression ratio at 11dB compared with that of the 18 N X Mai, …, N H Hoang, “Proposed methods for … GNSS anti-interference devices.” Research algorithm of processing signal space without correction The Frost two stage algorithms are significantly worse than the above algorithm for noise resistance The study on two-stage STAP algorithms based on automatic clearing of heterogeneous collection channels confirms their effectiveness Particularly for adaptive phase array antennas with elements, when channels are heterogeneous, the SINR at the output is within the range (11.5 21)dB (when the SINR ratio at the input 60dB ) for all noise cases that is an extremely good results The study of compensated autonomous units with automatic correction circuits indicates their high efficiency in conditions of heterogeneous receiver channels such as for 7-element phase array antennas In particular, the case for phase array antenna model of elements have been considered, neither the loss of noise value compared to the space-time filter nor the loss of the SINR ratio at the output is too much In severe noise conditions, for two-phase array antennas, the corresponding losses are not greater than 11dB and 4dB Then the SINR ratio of the auto-calibrated compensator does not fall below 22dB which is perfectly suited to protect the user's positioning devices REFERENCES [1] Applebaum S.P “Adaptive arrays” // IEEE Trans Antennas propagation Sept 1976 V AP-24 R 585-598 [2] Frost.0 L., III, “An Algorithm for Linearly Constrained Adaptive Array Processing,” PROC IEEE, Vol 60, pp 926-935, Aug 1972 [3] Ngô Xuân Mai, Hoàng Thế Khanh, Lê Kỳ Biên “Non-Working zones in GNSS at interference protection” Антенны, pp.37-47, № 4.2017 [4] Fante R.L., Fitzgibbons M.P., McDonald K.F Effect of adaptive array processing on GPS signal crosscorrelation // www.mitre-corporation.com October 2004 [5] Widrow B., “A Review of Adaptive Antennas” vol 66 Springer (1979) [6] Robert C Hansen., Phased Array Antennas, John Wiley & sons, Inc., 2001 [7] Tobias Kersten “On the Impact of Group Delay Variations on GNSS Time and Frequency Transfer” 978-14673-1923-2/12 2012 IEEE [8] Pisoni, F.; Mattos, P.G., "Compensation of Group Delay Differences in the GNSS Receiver Front End", Institute of Navigation (ION GNSS 2012), Nashville, Tennessee, September 2012, (in press) [9] Fabio Pisoni, Dr Philip G Mattos, “Correction of pseudorange errors in Galileo and GLONASS caused by biases in group delay”, 978-1-4673-2011-5/12 ©2012 IEEE [10] Lixun Li, Yingxue Su, Baiyu Li, Feixue Wang., “Phase and Group delay Analysis for Patch Antenna” IEEE, 2/2015 [11] Davide Margaria, Emanuela Falletti., “Impact of the Group Delay on BOC(M,N) Tracking”, IEEE, 978-1-4799-0486-0/13 2013 IEEE [12] Lixun Li, Baiyu Li, Huaming Chen, Feixue Wang, “GNSS Antenna Phase Center and Group Delay Evaluating” IEEE, 978-1-4799-8897-6/15 2015 IEEE [13] Ngơ Xn Mai, Hồng Thế Khanh, Nguyễn Huy Hồng “Vùng khơng hoạt động máy thu định vị tồn cầu GNSS có chống nhiễu với ăng-ten mảng phần tử”, Tạp chí Nghiên cứu khoa học công nghệ quân sự, Viện KH-CN QS, số 53-2/2018, tr 61-70 [14] Ngơ Xn Mai, Hồng Thế Khanh, Nguyễn Huy Hoàng, Lê Thị Trang, “Nghiên cứu ảnh hưởng tính khơng đồng kênh thu tới hiệu chống nhiễu thu tín hiệu vệ tinh GPS/GLONASS ăng-ten mảng pha”, Hội thảo quốc gia Journal of Military Science and Technology, Special Issue, No.60A, 05 - 2019 19 Electronics & Automation “Ứng dụng công nghệ cao vào thực tiễn” , Tạp chí Viện KHCN-QS, Số đặc san FEE2018, 8-2018, tr.164-171 [15] Lixun Li, Yingxue Su, Baiyu Li, Feixue Wang, “Phase and Group delay Analysis for Patch Antenna”, 978-1-4799-8767-2/15 2015 IEEE [16] Anurag Raghuvanshi and Frank van Graas, “Impact of Antenna Group Delay Variations on Protection Levels”, 978-1-5090-2042-3/16 © 2016 IEEE TÓM TẮT ĐỀ XUẤT CÁC PHƯƠNG PHÁP SỬA LỖI KHÔNG ĐỒNG NHẤT CỦA KÊNH THU CHO CÁC THIẾT BỊ CHỐNG NHIỄU GNSS Bài báo trình bày kết nghiên cứu tác giả việc sửa lỗi kênh không đồng ăng-ten mạng pha nhằm nâng cao chất lượng chổng nhiễu cho thiết bị đầu cuối hệ thống định vị dẫn đường vệ tinh Các phương pháp sửa lỗi mà tác giả đề xuất thuật toán hai giai đoạn với tự động hiệu chỉnh thuật toán sửa lỗi sở tự bù trừ Từ khóa: Khơng đồng kênh thu; Chống nhiễu GNSS; Giữ chậm theo nhóm Received 20th March, 2019 Revised 04th April, 2019 Accepted 15th May, 2019 Address:1 Electronic Institute, Academy of Military science and technology; Hitech Telecommunication Center, Military signal Corps; Misile Institute, Academy of Military science and technology; Military Technical Academy * Email: ngomaicnc@gmail.com 20 N X Mai, …, N H Hoang, “Proposed methods for … GNSS anti-interference devices.” ... Proposed methods for … GNSS anti- interference devices. ” Research receiver channels are 50, 0.5dB, 200kHz, respectively The correlation interval is heterogeneous and the frequency response of. .. Therefore, we may conclude that 16 N X Mai, …, N H Hoang, Proposed methods for … GNSS anti- interference devices. ” Research the two proposed algorithms are fully efficient even when the channel. .. 11dB compared with that of the 18 N X Mai, …, N H Hoang, Proposed methods for … GNSS anti- interference devices. ” Research algorithm of processing signal space without correction The Frost two