一种基于全相位FFT幅值的频率补偿方法

doi:10.11959/j.issn.2096-3750.2022.00274

Abstract

Abstract:

Distance measurement is an important part of the wireless location technology.The ranging accuracy of millimeter wave based distance measurement depends on the frequency estimation accuracy of beat signals from the targets, but the existing frequency estimation algorithms have the shortcomings of either high complexity or low accuracy.In order to improve the ranging accuracy, the frequency compensation value and frequency estimation method based on all phase FFT amplitude was proposed to improve the performance of frequency estimation.Firstly, the signal amplitude was estimated based on the relationship between its all phase FFT and its conventional FFT spectrum.Moreover, using the relationship between the estimated signal amplitude, the signal spectrum amplitude and frequency compensation value, the frequency compensation value was solved by Newton iterative algorithm.Then, the frequency compensation value was used to shift the frequency of the signal, and the frequency compensation value was estimated again to obtain the final estimation value of the signal frequency, from which the distance of the target was calculated.Finally, simulation results were presented to show that the proposed method has higher distance measurement accuracy than the existing methods.

Key words: millimeter wave, localization, distance measurement, frequency estimation

CLC Number:

TN958.94

Yingjie ZHU, Wuxiong ZHANG, Huiyue YI, Hui XU. A frequency offset compensation method based on all phase FFT amplitude[J]. Chinese Journal on Internet of Things, 2022, 6(2): 10-18.

Figures/Tables 8

算法	复数乘法	复数加法
FFT算法	$\frac{N}{2} lb N$	$N lb N$
补零FFT算法	$\frac{M N}{2} lb M N$	$MNlb M N$
CZT算法	$\frac{N}{2} lb N + M N$	$N lb N + M N - 1$
Rife算法	$\frac{N}{2} lb N$	$Nlb N$
M-Rife算法^[8]	$\frac{N}{2} lb N + 2 N$	$N lb N + \frac{4}{3} N$
改进Rife算法^[11]	$\frac{N}{2} lb N + 2 N$	$\frac{N}{2} lb N + 2 N - 1$
Zoom-FFT算法	$N lb N$	$2 N lb N$
所提算法	$\frac{N}{2} lb N + 5 N$	$N lb N + 5 N - 1$

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N	FFT	补零FFT	CZT	Rife	M-Rife^[8]	改进Rife^[11]	Zoom-FFT	所提算法
512	0.002 547	0.010 987	0.025 309	0.002 553	0.002 555	0.003 031	0.005 987	0.003 836
1 024	0.005 176	0.022 754	0.060 590	0.005 179	0.005 182	0.006 184	0.012 721	0.007 815
2 048	0.010 510	0.046 963	0.137 543	0.010 512	0.010 515	0.012 647	0.028 644	0.016 064
4 096	0.021 458	0.099 251	0.301 047	0.021 461	0.021 468	0.026 017	0.069 771	0.033 138
8 192	0.044 903	0.209 558	0.652 962	0.044 905	0.044 921	0.054 532	0.196 047	0.069 478

SNR/dB	FFT	补零FFT	CZT	Rife	M-Rife^[8]	改进Rife^[11]	Zoom-FFT	所提算法
-14	8.548 188	8.503 611	8.502 328	8.512 713	8.512 422	8.512 422	8.636 658	8.502 083
-12	8.546 224	8.505 676	8.500 008	8.505 831	8.505 706	8.505 706	8.521 796	8.499 737
-10	8.546 231	8.507 104	8.499 979	8.502 519	8.502 508	8.502 508	8.502 623	8.499 712
-8	8.546 231	8.508 234	8.500 057	8.500 774	8.500 774	8.500 774	8.503 525	8.499 897
-6	8.546 231	8.508 600	8.499 966	8.499 999	8.499 999	8.499 999	8.505 530	8.499 880
-4	8.546 231	8.508 731	8.500 052	8.499 993	8.499 993	8.499 993	8.507 097	8.499 998
-2	8.546 231	8.508 748	8.500 013	8.499 985	8.499 985	8.499 985	8.508 189	8.499 994
0	8.546 231	8.508 748	8.499 956	8.499 983	8.499 983	8.499 983	8.508 611	8.499 992
2	8.546 231	8.508 748	8.499 875	8.499 987	8.499 987	8.499 987	8.508 737	8.499 994
4	8.546 231	8.508 748	8.499 796	8.499 996	8.499 996	8.499 996	8.508 748	8.499 997
6	8.546 231	8.508 748	8.499 726	8.500 005	8.500 005	8.500 005	8.508 748	8.500 002
8	8.546 231	8.508 748	8.499 698	8.499 990	8.499 990	8.499 990	8.508 748	8.499 992
10	8.546 231	8.508 748	8.499 692	8.500 002	8.500 002	8.500 002	8.508 748	8.500 001
12	8.546 231	8.508 748	8.499 692	8.500 001	8.500 001	8.500 001	8.508 748	8.499 999
14	8.546 231	8.508 748	8.499 692	8.499 998	8.499 998	8.499 998	8.508 748	8.499 999

SNR/dB	FFT	补零FFT	CZT	Rife	M-Rife^[8]	改进Rife^[11]	Zoom-FFT	所提算法
-14	0.311 758	0.013 086	0.312 130	0.313 985	0.313 977	0.313 977	2.001 150	0.312 081
-12	0.001 060	0.010 302	0.007 481	0.025 285	0.025 203	0.025 203	0.688 125	0.008 248
-10	0.000 000	0.007 675	0.006 050	0.017 482	0.017 471	0.017 471	0.105 097	0.006 406
-8	0.000 000	0.004 357	0.004 830	0.010 477	0.010 477	0.010 477	0.013 244	0.004 816
-6	0.000 000	0.002 351	0.003 912	0.005 356	0.005 356	0.005 356	0.010 508	0.003 717
-4	0.000 000	0.000 795	0.003 257	0.003 340	0.003 340	0.003 340	0.007 692	0.002 967
-2	0.000 000	0.000 000	0.002 656	0.002 619	0.002 619	0.002 619	0.004541	0.002 321
0	0.000 000	0.000 000	0.002 070	0.002 033	0.002 033	0.002 033	0.002 260	0.001 846
2	0.000 000	0.000 000	0.001 474	0.001 627	0.001 627	0.001 627	0.000 649	0.001 469
4	0.000 000	0.000 000	0.000 914	0.001 296	0.001 296	0.001 296	0.000 000	0.001 170
6	0.000 000	0.000 000	0.000 471	0.001 026	0.001 026	0.001 026	0.000 000	0.000 930
8	0.000 000	0.000 000	0.000 183	0.000 816	0.000 816	0.000 816	0.000 000	0.000 739
10	0.000 000	0.000 000	0.000 000	0.000 646	0.000 646	0.000 646	0.000 000	0.000 582
12	0.000 000	0.000 000	0.000 000	0.000 511	0.000 511	0.000 511	0.000 000	0.000 462
14	0.000 000	0.000 000	0.000 000	0.000 407	0.000 407	0.000 407	0.000 000	0.000 366

A frequency offset compensation method based on all phase FFT amplitude

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