Re: Time to scrap SETI?

From: news.vif.com (root_at_NoReply-AntiSpam.com)
Date: 12/19/04 

Date: Sun, 19 Dec 2004 06:55:45 -0500

SHUT THE *** ALREADY! WHO *** CARES

David Woolley wrote:

> In article <CmSwd.204$5R.135@newssvr21.news.prodigy.com>,
> Rob Dekker <rob@verific.com> wrote:
>
>
>>the data transfer will occur in some (limited) bandwidth, or (in case of
>>true spread-spectrum transmission) in limited time (very short pulses).
>
>
> I assume you mean direct sequence, rather than frequency hopping,
> spread spectrum. That is normally sent with no gaps between pulses.
> If you know the spreading code and rate, you can still achieve good signal
> to noise ratios, but it is not susceptible to S@H type pulse analysis.
> (Actually, the theoretical throughput of a channel using a very large
> bandwidth and very weak signal is higher than that using a very strong
> signal in a small bandwidth, assuming a constant power spectral density
> for the noise, and idealised noise - see below.)
>
>
>>Either way, ANY communication signal, no matter how intelligent the designer
>>was, will be distinguishable from natural thermal noise, which is neither
>
>
> Natural noise isn't just thermal.
>
>
>>limited in bandwidth, nor in time.
>
>
> The most fundamental problem here is that more than half the power in
> an AM (double side band, full carrier) signal is wasted in the carrier,
> even when fully modulated. That carrier can easily be well under 0.1Hz
> wide and approach the theoretical limits for spectrum spreading in
> interstellar space. That means that most of an AM signal is available
> with only the noise contribution from 0.1Hz of bandwidth.
>
> With more efficient methods, the power is spread across the whole channel,
> which will be several hundred Hz wide for telephone quality digital
> speech, even using the most bandwidth efficient codings normally used,
> and much more for typical mobile phone applications. That means that you
> have 1,000s to 100,000s of times the noise in the receiver compared with
> an AM carrier. That's a penalty of 30 to 300 in the detectable power
> (this is for detecting presence, not recovering the signal). Speech is
> a relatively poor example, because relatively little power is used for
> telephone quality speech. For TV, the power is spread over several MHz,
> giving a detection penalty of several 1000 to 1.
>
> These detection scenarios assume that:
>
> 1) the channel exists in isolation (in reality there will be many channels
> adjacent to each other, and whilst they may currently have guard bands
> between them, these are reducing as technology gets better).
>
> 2) the signal is narrow enough that one can assume the sky noise doesn't
> vary across the channel
>
>
>>Besides that, there are applications where the data rate is very low.
>>Surveillance radar is one example. For surveillance radar, you only need to
>>know if there is an object or not. That is only one bit of information.
>
>
> That represents a misunderstanding about the information theory definition
> of a bit. One is actually interested in knowing that the target is:
>
> - at a particular range;
> - at a particular time;
> - of a particular approximate size;
> - has a particular range;
> - (in a particular direction and with a particular angular velocity).
>
> That requires quite a lot of bits.
>
> A bit in information theory is not the same as a Boolean in a programming
> language; it represents relative probabilities; the existence of an
> improbable event conveys many more bits of information than the common case.
> It is that definition of bit that determines the required SNR (and that
> definition of bit that means that S@H has to have a detection threshold of
> 22 times mean noise, not of 1 times mean noise).
>
>
>>Intelligently designed radar systems will use this to be either very limited
>>in bandwidth and/or in time, but always within the limit :
>
>
>> data=SNR*time/bandwidth
>
>
> The correct formula (Shannon-Hartley theorem) is:
>
> <theoretical max data rate> = <bandwidth> * log2 (1 + <SNR>)
>
> One can't, strictly speaking, simply multiply this by time (the
> formula is the asymptotic one for infinite time), although
> for a reasonably long time period you will get quite close, but with
> a finite error rate:
>
> ~ data = log2 (1 + SNR) * time * bandwidth
>
> (Note no divisions.)
>
> Typical applications of surveillance radar require that results be
> provided promptly, so channel capacity has to be much higher than
> that needed to support the long term average data rate. This is
> partially mitigated, in air defence radars by having separate tracking
> and acquisition modes, so that an acquired target is not diluted by
> observations of empty space.
>
> In practice, relatively low power primary surveillance radars do use
> short pulse. These have to be short enough to give good range resolution,
> resulting in a large signal bandwidth. For military applications, these
> pulses will not be at fixed intervals, because that makes jamming more
> difficult and because fixed intervals can result in aliasing of Doppler
> rates that may make a target appear not to be moving at an interesting
> speed. The lack of fixed intervals will make S@H type pulse detection
> unworkable.
>
> Very high power surveillance radars (always, I believe) and planetary
> radar in ranging mode transmit pseudo random sequences at constant
> power and then despread the result. That allows them to use much lower
> peak powers.
>
> Air surveillance radars will get a lot of their noise from ground clutter,
> rather than the nice well behaved noise that the channel capacity
> formulae assume. 

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