diff --git a/applications/lofar2/model/signal_statistics.ipynb b/applications/lofar2/model/signal_statistics.ipynb index c90858b30b427b8e2309e7caed3722bfa052b7ec..4a1f8fbc19bb9b89aad3bd2aadc7b49fab78a42f 100644 --- a/applications/lofar2/model/signal_statistics.ipynb +++ b/applications/lofar2/model/signal_statistics.ipynb @@ -12,9 +12,9 @@ "Purpose: Model the SNR of a beamformer and a correlator\n", "\n", "Status:\n", - "* coherent, voltage beamformer: I think I understand how it improves SNR by sqrt(N_ant)\n", - "* incoherent, power beamformer: TODO, but I do not understand yet how N_ant > 1 can improve SNR\n", - "* correlator: started, but I do not understand yet how N_int > 1 can improve SNR and what is the limit\n", + "* coherent summator (= voltage beamformer): SNR of coherent input improves by the number of inputs N\n", + "* incoherent summator (= auto correlation, power beamformer): SNR does not improve, but accuracy of power mean measurement (its variance) does improves by factor N. Summing powers from N inputs or summing N powers from one input is equivalent.\n", + "* correlator: SNR of coherent input improves by sqrt(N) for integration over N cross powers in time. Hence if the input SNR of the input signal is -20 dB (i.e. sigma_coh / sigma_sys = 0.1) then it takes N = 10000 to improve the SNR by a factor 100 = +20 dB to 0 dB.\n", "\n", "References:\n", "\n", @@ -23,7 +23,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 1, "id": "2b477516", "metadata": {}, "outputs": [], @@ -48,12 +48,16 @@ "Coherent and incoherent signals. With S signals, the std of their sum:\n", " \n", "* increases by S for coherent signals\n", - "* increases by sqrt(S) for incoherent signals" + "* increases by sqrt(S) for incoherent signals\n", + "\n", + "Coherent averaging by summing the signal voltages improves the SNR of a signal by a factor N^2 / N = N, because the signal power increases by a factor N^2, while the incoherent noise adds as powers, so the noise power increases by a factor N.\n", + "\n", + "Incoherent averaging by summing the signal powers does not improve the SNR, because the phase information of the signal is lost in the powers. Incoherent averaging does reduce the variance of the signal power estimate by a factor N, so it mkes the measurement more accurate." ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 2, "id": "9c55fb7b", "metadata": {}, "outputs": [], @@ -70,7 +74,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 3, "id": "74edfe32", "metadata": {}, "outputs": [ @@ -78,9 +82,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "mean(si) = -0.199151, expected -0.2\n", + "mean(si) = -0.207540, expected -0.2\n", "std(si) = 0.500000, expected 0.5\n", - "rms(si) = 0.538202, expected 0.538516\n" + "rms(si) = 0.541362, expected 0.538516\n" ] } ], @@ -105,12 +109,12 @@ "id": "17d333f1", "metadata": {}, "source": [ - "## 2 Beamforming\n", + "## 2 Summator\n", "\n", "Two types:\n", "\n", - "1. Coherent, voltage beamformer (e.g. digital BF in LOFAR2 Station, TAB in ARTS)\n", - "2. Incoherent, power beamformer (e.g. IAB in ARTS)" + "1. Coherent summation in voltage beamformer (e.g. digital BF in LOFAR2 Station, TAB in ARTS)\n", + "2. Incoherent summation in power beamformer (e.g. IAB in ARTS)" ] }, { @@ -118,27 +122,26 @@ "id": "96de4cb4", "metadata": {}, "source": [ - "### 2.1 Coherent, voltages beamformer (BF)\n", + "### 2.1 Coherent summation (voltages beamformer)\n", "\n", "Two signal input types:\n", " \n", "1. Coherent signals, add up as voltages\n", "2. Incoherent signal, add up as power\n", "\n", - "In the voltage beamformer the weak signal in the beamlet adds coherently and the sky\n", - "signals from other directions add incoherently. Hence the SNR of the weak signal in\n", - "the BF output improves by factor S/sqrt(S) = sqrt(S)." + "In the voltage beamformer the sky signal in the beamlet direction adds coherently and the sky\n", + "signals from other directions and from the receivers noise add incoherently. Hence the SNR of the beamlet signal improves by factor S/sqrt(S) = sqrt(S)." ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 4, "id": "89845ec3", "metadata": {}, "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] @@ -150,7 +153,7 @@ }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] @@ -164,56 +167,58 @@ "source": [ "# Signal inputs\n", "# . Warning: do use not too high values for N_samples and S_max to avoid too long compute time.\n", - "N_samples = 1000\n", - "S_max = 200\n", + "N_samples = 10000 # >= 3\n", + "S_max = 100\n", "S_arr = np.arange(1, S_max + 1)\n", + "S_arr_log = np.log10(S_arr)\n", "\n", - "sigma_weak = 0.05\n", - "sigma_other = 0.5\n", + "sigma_coh = 0.05\n", + "sigma_incoh = 0.5\n", "\n", - "si_weak = np.random.randn(N_samples)\n", - "si_weak *= sigma_weak / np.std(si_weak)\n", + "si_coh = np.random.randn(N_samples)\n", + "si_coh *= sigma_coh / np.std(si_coh)\n", "\n", - "# Beamformer sum(S)\n", - "bf_weak_std_arr = []\n", - "bf_other_std_arr = []\n", + "# Voltage beamformer sum(S)\n", + "bf_coh_std_arr = []\n", + "bf_incoh_std_arr = []\n", "bf_sys_std_arr = []\n", - "bf_SNR_dB_arr = []\n", + "coh_SNR_dB_arr = []\n", "for S in S_arr:\n", - " # The weak signal in the beamlet adds coherently for all signal inputs\n", - " bf_weak = S * si_weak\n", - " bf_weak_std = np.std(bf_weak)\n", - " bf_weak_std_arr.append(bf_weak_std)\n", + " # The coh signal in the beamlet direction adds coherently for all signal inputs\n", + " bf_coh = S * si_coh\n", + " bf_coh_std = np.std(bf_coh)\n", + " bf_coh_std_arr.append(bf_coh_std)\n", " \n", - " # The other signals from other directions add incoherently\n", - " bf_other = np.zeros(N_samples)\n", + " # The incoh signals from other directions and from the receivers noise add incoherently\n", + " bf_incoh = np.zeros(N_samples)\n", " for si in range(1, S + 1):\n", - " si_other = np.random.randn(N_samples)\n", - " si_other *= sigma_other / np.std(si_other)\n", - " bf_other += si_other\n", - " bf_other_std = np.std(bf_other)\n", - " bf_other_std_arr.append(bf_other_std)\n", + " si_incoh = np.random.randn(N_samples)\n", + " si_incoh *= sigma_incoh / np.std(si_incoh)\n", + " bf_incoh += si_incoh\n", + " bf_incoh_std = np.std(bf_incoh)\n", + " bf_incoh_std_arr.append(bf_incoh_std)\n", " \n", " # Total BF output\n", - " bf_sys_std = np.std(bf_weak + bf_other)\n", + " bf_sys_std = np.std(bf_coh + bf_incoh)\n", " bf_sys_std_arr.append(bf_sys_std)\n", " \n", - " SNR_dB = 20 * np.log10(bf_weak_std / bf_other_std)\n", - " bf_SNR_dB_arr.append(SNR_dB)\n", + " # SNR of the coherent sum\n", + " coh_SNR_dB = 20 * np.log10(bf_coh_std / bf_incoh_std)\n", + " coh_SNR_dB_arr.append(coh_SNR_dB)\n", "\n", "plt.figure(1)\n", - "plt.plot(S_arr, bf_weak_std_arr, 'g', S_arr, bf_other_std_arr, 'b', S_arr, bf_sys_std_arr, 'r')\n", - "plt.title(\"Beamformer\")\n", + "plt.plot(S_arr, bf_coh_std_arr, 'g', S_arr, bf_incoh_std_arr, 'b', S_arr, bf_sys_std_arr, 'r')\n", + "plt.title(\"Summator\")\n", "plt.xlabel(\"Number of signal inputs\")\n", "plt.ylabel(\"BF std\")\n", - "plt.legend(['bf_weak', 'bf_other', 'bf_sys'])\n", + "plt.legend(['bf_coh', 'bf_incoh', 'bf_sys'])\n", "plt.grid()\n", "\n", "plt.figure(2)\n", - "plt.plot(S_arr, bf_SNR_dB_arr, 'r')\n", - "plt.title(\"Beamformer\")\n", - "plt.xlabel(\"Number of signal inputs\")\n", - "plt.ylabel(\"SNR [dB]\")\n", + "plt.plot(S_arr_log, coh_SNR_dB_arr, 'r-o')\n", + "plt.title(\"Summator\")\n", + "plt.xlabel(\"Number of signal inputs (log10)\")\n", + "plt.ylabel(\"SNR of voltage signal [dB]\")\n", "plt.grid()" ] }, @@ -223,7 +228,9 @@ "metadata": {}, "source": [ "**Conclusion:**\n", - "The voltage beamformer improves the SNR of the weak signal by factor sqrt(S). For most very weak astronimical signals this is not enough to make them appear above the system noise, so then additional beamforming is needed or integration in time using a correlator." + "The voltage beamformer improves the SNR of the beamlet signal by factor S, because the coherent signal power increases by S^2 while the incoherent noise power increases by S. For very weak astronomical signals this SNR improvement is not enough to make them appear above the system noise, so then additional beamforming is needed or integration in time using a correlator is needed.\n", + "\n", + "The averaging over N_samples in time does not improve the SNR of the beamlet signal, but it does improve the accuracy of the SNR measurement by a factor N_samples. Hence this model shows two different SNR measures, one regarding the SNR of the coherent beamlet signal (depending on S) and one regarding the SNR measurement itself (depending on N_samples)." ] }, { @@ -231,17 +238,15 @@ "id": "9dafd903", "metadata": {}, "source": [ - "### 2.2 Incoherent, powers beamformer\n" + "### 2.2 Incoherent summation (powers beamformer)\n" ] }, { - "cell_type": "code", - "execution_count": 26, - "id": "499d7eb6", + "cell_type": "markdown", + "id": "fd6ffb94", "metadata": {}, - "outputs": [], "source": [ - "# TODO" + "Incoherent summation of powers from S inputs is equivalent to incoherent summation of S powers in time from a single input. Therefore the incoherent summation does not improve the SNR of the signal, but it does improve the accuracy of the power measurement by a factor S. Hence instead of measuring with one dish for S intervals it is equivalent to sum the powers of S dishes for 1 interval. Hence the field of view of the summed power beam is the same as the field of view of one dish." ] }, { @@ -252,9 +257,141 @@ "## 3 Correlation\n" ] }, + { + "cell_type": "markdown", + "id": "94dce0e2", + "metadata": {}, + "source": [ + "### 3.1 Auto powers" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "8713e865", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Number of samples N_samples in time for input A, try N_samples in N_samples_arr\n", + "N_steps = 1000\n", + "\n", + "N_min = 10\n", + "N_max = 100000\n", + "n_incr = (N_max / N_min)**(1 / N_steps)\n", + "N_samples_arr = []\n", + "for s in range(N_steps + 1):\n", + " n = int(N_min * n_incr**s)\n", + " N_samples_arr.append(n)\n", + " \n", + "N_samples_arr_log = np.log10(N_samples_arr)\n", + "\n", + "# Input signal\n", + "sigma = 1.0\n", + "pow_mean = sigma**2\n", + "\n", + "# Auto correlator mean(A * A)\n", + "auto_mean_arr = []\n", + "auto_std_arr = []\n", + "measure_SNR_arr = []\n", + "measure_SNR_dB_arr = []\n", + "for N_samples in N_samples_arr:\n", + " # Signal input A\n", + " sA = np.random.randn(N_samples)\n", + " sA *= sigma / np.std(sA)\n", + "\n", + " # Auto correlate A\n", + " auto_mean = np.mean(sA * sA)\n", + " auto_mean_arr.append(auto_mean)\n", + " auto_std = np.std(sA * sA)\n", + " auto_std_arr.append(auto_std)\n", + "\n", + " # Accuracy of the power measurement\n", + " measure_SNR = auto_mean / np.abs(auto_mean - pow_mean)\n", + " measure_SNR_dB = 10 * np.log10(measure_SNR)\n", + " measure_SNR_arr.append(measure_SNR)\n", + " measure_SNR_dB_arr.append(measure_SNR_dB)\n", + " \n", + " #print(f\"{N_samples}, {auto_mean:9.6f}, {auto_std:9.6f}, {measure_SNR_dB:.0f}\")\n", + "\n", + "plt.figure(1)\n", + "plt.plot(N_samples_arr, auto_mean_arr, 'g')\n", + "plt.title(\"Auto correlator mean\")\n", + "plt.xlabel(\"Number of samples\")\n", + "plt.ylabel(\"Auto power mean\")\n", + "plt.grid()\n", + "\n", + "plt.figure(2)\n", + "plt.plot(N_samples_arr, auto_std_arr, 'g')\n", + "plt.title(\"Auto correlator std\")\n", + "plt.xlabel(\"Number of samples\")\n", + "plt.ylabel(\"Auto power std\")\n", + "plt.grid()\n", + "\n", + "plt.figure(3)\n", + "plt.plot(N_samples_arr_log, measure_SNR_dB_arr, 'r')\n", + "plt.title(\"Auto correlator\")\n", + "plt.xlabel(\"Number of samples (log10)\")\n", + "plt.ylabel(\"SNR of power measurement [dB]\")\n", + "plt.grid()" + ] + }, + { + "cell_type": "markdown", + "id": "5f5e3a0d", + "metadata": {}, + "source": [ + "**Conclusion:**\n", + "The summation of power values does not improve the SNR, but it does improve the accuracy of the power measurement. Therefore the SNR for the auto correlation is defined as the accuracy of the mean power measurement. This SNR improves by N." + ] + }, + { + "cell_type": "markdown", + "id": "f4be5736", + "metadata": {}, + "source": [ + "### 3.2 Cross powers" + ] + }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 16, "id": "470fd269", "metadata": {}, "outputs": [ @@ -262,12 +399,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "SNR input = -10.458 dB\n" + "SNR input = -20.000 dB\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] @@ -279,7 +416,7 @@ }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] @@ -291,7 +428,7 @@ }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] @@ -303,98 +440,121 @@ } ], "source": [ - "# Signal inputs\n", + "# Number of samples N_samples in time for input A and input B, try N_samples in N_samples_arr\n", "N_steps = 100\n", "\n", "N_min = 10\n", - "N_max = 10000\n", + "N_max = 10000000\n", "n_incr = (N_max / N_min)**(1 / N_steps)\n", - "N_arr = []\n", + "N_samples_arr = []\n", "for s in range(N_steps + 1):\n", " n = int(N_min * n_incr**s)\n", - " N_arr.append(n)\n", + " N_samples_arr.append(n)\n", + "N_samples_arr_log = np.log10(N_samples_arr)\n", "\n", - "sigma_weak = 0.3\n", - "sigma_other = 1.0\n", + "# Input signal\n", + "sigma_coh = 0.1\n", + "pow_coh = sigma_coh**2\n", + "sigma_incoh = 1.0\n", "\n", - "SNR_dB = 20 * np.log10(sigma_weak / sigma_other)\n", - "print(f\"SNR input = {SNR_dB:.3f} dB\")\n", + "input_SNR = (sigma_coh / sigma_incoh)**2\n", + "input_SNR_dB = 10 * np.log10(input_SNR)\n", + "print(f\"SNR input = {input_SNR_dB:.3f} dB\")\n", "\n", "# Correlator mean(A * B)\n", - "cor_weak_mean_arr = []\n", - "cor_weak_std_arr = []\n", - "cor_other_mean_arr = []\n", - "cor_other_std_arr = []\n", - "cor_sys_mean_arr = []\n", - "cor_sys_std_arr = []\n", - "cor_SNR_arr = []\n", - "cor_SNR_dB_arr = []\n", - "for N in N_arr:\n", - " si_weak = np.random.randn(N)\n", - " si_weak *= sigma_weak / np.std(si_weak)\n", + "cross_coh_mean_arr = []\n", + "cross_coh_std_arr = []\n", + "cross_incoh_mean_arr = []\n", + "cross_incoh_std_arr = []\n", + "cross_sys_mean_arr = []\n", + "cross_sys_std_arr = []\n", + "cross_SNR_arr = []\n", + "cross_SNR_dB_arr = []\n", + "for N_samples in N_samples_arr:\n", + " si_coh = np.random.randn(N_samples)\n", + " si_coh *= sigma_coh / np.std(si_coh)\n", "\n", " # Signal input A\n", - " sA_other = np.random.randn(N)\n", - " sA_other *= sigma_other / np.std(sA_other)\n", - " sA_sys = sA_other + si_weak\n", + " sA_incoh = np.random.randn(N_samples)\n", + " sA_incoh *= sigma_incoh / np.std(sA_incoh)\n", + " sA_sys = sA_incoh + si_coh\n", "\n", " # Signal input B\n", - " sB_other = np.random.randn(N)\n", - " sB_other *= sigma_other / np.std(sB_other)\n", - " sB_sys = sB_other + si_weak\n", + " sB_incoh = np.random.randn(N_samples)\n", + " sB_incoh *= sigma_incoh / np.std(sB_incoh)\n", + " sB_sys = sB_incoh + si_coh\n", " \n", " # Correlate A and B\n", - " cor_weak_mean = np.mean(si_weak * si_weak)\n", - " cor_weak_mean_arr.append(cor_weak_mean)\n", - " cor_weak_std = np.std(si_weak * si_weak)\n", - " cor_weak_std_arr.append(cor_weak_std)\n", - " cor_other_mean = np.mean(sA_other * sB_other)\n", - " cor_other_mean_arr.append(cor_other_mean)\n", - " cor_other_std = np.std(sA_other * sB_other)\n", - " cor_other_std_arr.append(cor_other_std)\n", - " cor_sys_mean = np.mean(sA_sys * sB_sys)\n", - " cor_sys_mean_arr.append(cor_sys_mean)\n", - " cor_sys_std = np.std(sA_sys * sB_sys)\n", - " cor_sys_std_arr.append(cor_sys_std)\n", - " #print(f\"{N}, {cor_weak_mean:9.6f}, {cor_other_mean:9.6f}, {cor_sys_mean:9.6f}\")\n", - " #print(f\"{N}, {cor_weak_std:9.6f}, {cor_other_std:9.6f}, {cor_sys_std:9.6f}\")\n", - "\n", - " SNR = np.abs(cor_weak_mean / cor_other_mean)\n", - " SNR_dB = 10 * np.log10(SNR)\n", - " cor_SNR_arr.append(SNR)\n", - " cor_SNR_dB_arr.append(SNR_dB)\n", - " #print(f\"{N}, SNR output = {SNR_dB:.0f} dB\")\n", + " cross_coh_mean = np.mean(si_coh * si_coh)\n", + " cross_coh_mean_arr.append(cross_coh_mean)\n", + " cross_coh_std = np.std(si_coh * si_coh)\n", + " cross_coh_std_arr.append(cross_coh_std)\n", + " cross_incoh_mean = np.mean(sA_incoh * sB_incoh)\n", + " cross_incoh_mean_arr.append(cross_incoh_mean)\n", + " cross_incoh_std = np.std(sA_incoh * sB_incoh)\n", + " cross_incoh_std_arr.append(cross_incoh_std)\n", + " cross_sys_mean = np.mean(sA_sys * sB_sys)\n", + " cross_sys_mean_arr.append(cross_sys_mean)\n", + " cross_sys_std = np.std(sA_sys * sB_sys)\n", + " cross_sys_std_arr.append(cross_sys_std)\n", + " #print(f\"{N_samples}, {cross_coh_mean:9.6f}, {cross_incoh_mean:9.6f}, {cross_sys_mean:9.6f}\")\n", + " #print(f\"{N_samples}, {cross_coh_std:9.6f}, {cross_incoh_std:9.6f}, {cross_sys_std:9.6f}\")\n", + "\n", + " # SNR definitions of the coherent correlator\n", + " # . using cross_coh_mean shows the cross_SNR imrpovement for all N_max\n", + " # . using cross_sys_mean requires that N_max > input_SNR to see the improvement in cross_SNR,\n", + " # because for lower N_samples the cross_sys_mean is still dominated by cross_incoh_mean and\n", + " # then thus cross_SNR = 1\n", + " # . the cross_coh_mean and cross_sys_mean become pow_coh, so constant > 0. Therefor it is\n", + " # also possible to define relative cross_SNR using 1 divided by the error in cross_coh_mean\n", + " # or the value of cross_incoh_mean, which both go to zero.\n", + " cross_SNR = np.abs(cross_coh_mean / cross_incoh_mean)\n", + " #cross_SNR = np.abs(1 / (cross_coh_mean - pow_coh))\n", + " #cross_SNR = np.abs(1 / cross_incoh_mean)\n", + " cross_SNR = np.abs(cross_sys_mean / cross_incoh_mean)\n", + " #cross_SNR = np.abs(cross_sys_mean / (cross_sys_mean - cross_coh_mean))\n", + " cross_SNR_dB = 10 * np.log10(cross_SNR)\n", + " cross_SNR_arr.append(cross_SNR)\n", + " cross_SNR_dB_arr.append(cross_SNR_dB)\n", + " #print(f\"{N_samples}, correlator SNR = {cross_SNR_dB:.0f} dB\")\n", "\n", "plt.figure(1)\n", - "plt.plot(N_arr, cor_weak_mean_arr, 'g', N_arr, cor_other_mean_arr, 'b', N_arr, cor_sys_mean_arr, 'r')\n", + "plt.plot(N_samples_arr, cross_coh_mean_arr, 'g', N_samples_arr, cross_incoh_mean_arr, 'b', N_samples_arr, cross_sys_mean_arr, 'r')\n", "plt.title(\"Correlator mean\")\n", "plt.xlabel(\"Number of samples\")\n", "plt.ylabel(\"Cross power mean\")\n", - "plt.legend(['cor_weak', 'cor_other', 'cor_sys'])\n", + "plt.legend(['cross_coh', 'cross_incoh', 'cross_sys'])\n", "plt.grid()\n", "\n", "plt.figure(2)\n", - "plt.plot(N_arr, cor_weak_std_arr, 'g', N_arr, cor_other_std_arr, 'b', N_arr, cor_sys_std_arr, 'r')\n", + "plt.plot(N_samples_arr, cross_coh_std_arr, 'g', N_samples_arr, cross_incoh_std_arr, 'b', N_samples_arr, cross_sys_std_arr, 'r')\n", "plt.title(\"Correlator std\")\n", "plt.xlabel(\"Number of samples\")\n", "plt.ylabel(\"Cross power std\")\n", - "plt.legend(['cor_weak', 'cor_other', 'cor_sys'])\n", + "plt.legend(['cross_coh', 'cross_incoh', 'cross_sys'])\n", "plt.grid()\n", "\n", "plt.figure(3)\n", - "#plt.plot(N_arr, cor_SNR_arr, 'r')\n", - "plt.plot(N_arr, cor_SNR_dB_arr, 'r')\n", + "plt.plot(N_samples_arr_log, cross_SNR_dB_arr, 'r')\n", "plt.title(\"Correlator\")\n", - "plt.xlabel(\"Number of samples\")\n", - "#plt.ylabel(\"SNR\")\n", - "plt.ylabel(\"SNR [dB]\")\n", + "plt.xlabel(\"Number of samples (log10)\")\n", + "plt.ylabel(\"SNR of coherent correlator [dB]\")\n", "plt.grid()" ] }, + { + "cell_type": "markdown", + "id": "4fc1cbf5", + "metadata": {}, + "source": [ + "**Conclusion:**\n", + "The expected coherent cross power is pow_coh and the measurement of cross_coh_mean = pow_coh becomes more accurate when N_samples increases. The incoherent cross power is cross_incoh_mean and goes to zero. The SNR of the coherent correlator is proportional to 1 / cross_incoh_mean. Dividing by almost zero causes the SNR to fluctuate, but in general the SNR of the coherent signal improves by sqrt(N_samples)." + ] + }, { "cell_type": "code", "execution_count": null, - "id": "8713e865", + "id": "e271fe26", "metadata": {}, "outputs": [], "source": []